{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 问题描述\n",
    "运⾏课上给出的notebook的代码：\n",
    "1. 对连续型特征，可以用哪个函数可视化其分布？（给出你最常用的一个即可），并根据代码运行结果给出示例。\n",
    "2. 对两个连续型特征，可以用哪个函数得到这两个特征之间的相关性？根据代码运行结果，给出示例。\n",
    "3. 如果发现特征之间有较强的相关性，在选择线性回归模型时应该采取什么措施。\n",
    "4. 当采用带正则的模型以及采用随机梯度下降优化算法时，需要对输入（连续型）特征进行去量纲预处理。课程代码给出了用标准化（StandardScaler）的结果，请改成最小最大缩放（MinMaxScaler）去量纲 ，并重新训练最小二乘线性回归、岭回归、和Lasso模型。\n",
    "5. 代码中给出了岭回归（RidgeCV）和Lasso（LassoCV）超参数（alpha_）调优的过程，请结合两个最佳模型以及最小二乘线性回归模型的结果，给出什么场合应该用岭回归，什么场合用Lasso，什么场合用最小二乘。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据描述： \n",
    "特征维数：13，每个特征的数据类型，非空值的样本数目\n",
    "1. CRIM：人均犯罪率 ；\n",
    "2. ZN：住宅用地的比例（对超过两万五千平方英尺的区域） ；整数\n",
    "3. INDUS：城镇中非零售营业比例；\n",
    "4. CHAS：是否靠近Charles河的边界；整数\n",
    "5. NOX：一氧化氮浓度 ；\n",
    "6. RM：住宅平均房间数；\n",
    "7. AGE：1940年之前建造的自住房屋的比例；\n",
    "8. DIS：距离波士顿五个中心的加权距离；\n",
    "9. RAD：高速公路的便利指数（索引）；整数\n",
    "10. TAX ：每一万美元财产的全额财产税率； 整数\n",
    "11. PTRATIO ：城乡师生比例；PTRATIO\n",
    "12. B ：黑人比例\n",
    "13. LSTAT ：低收入人群比例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.metrics import r2_score\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.linear_model import RidgeCV\n",
    "from sklearn.linear_model import LassoCV\n",
    "\n",
    "df = pd.read_csv(\"boston_housing.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 回答1. \n",
    "> 对于连续型特征，可以用seaborn的distplot方法对数值型特征绘制直方图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(df[\"MEDV\"], bins=30, kde=True)\n",
    "plt.xlabel(\"Median value of owner-occupied homes\", fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 回答2. \n",
    "> 对于两个连续型特征，可以用DataFrame的corr()方法先计算出每对特征间的相关矩阵，通常认为相关系数大于0.5的为强相关。以下用seaborn的heatmap()方法渲染出一个基于色彩编码的矩阵以展示结果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9590f788d0>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IS8vE39XZ5tgANx0R5QLQqlWU8NQT6u3KreSMAmlcDClk6HJfdMLNO2eQOYfM9JyXqvnMblSBpQFQh9fGcuc6mIxgMmI8fAhtlaoAWO7Fo/LPc7/5+2NNKNp/xp3bcW7SDJeXOuG9eAnei5eQFJeIb4h/ThqfIN9H+utIHn/FXIvmw55TmD9sLjLLiPVerFIWLz9kSh47zi6ogkujHzIT1ylLUYdWxKXvJFSlwpHJCViunlUmPgyfg/AJQIBdyjX2hRGgvFeuFXlwcXB0JRWbc0DdIvY9GGMIBxoJIToWZURKeRil9eEnpXzo6h0p5ddSynpSynrv9Hro+M1jcWTFVhZ1eJ9FHd7n4paj1Oz6DAAla4djTDWQVkjF0GrUKzi769n0wcqcbZYbl1AHlED4BYFag7ZBBKYT+3MPMqSTOrQrqaN7kDq6B5ZrF8iYP5nMn5eQNqU/aVP6Y468gjpIeSn41SlHVkoGhnz5G+4mY07LxK9OOQDCXm7G7c1K4y3veESp9vVIvhRFwsnrCBc96jLlwcUVbf0IhM4F653sQUpDBmkjXiFtfC/SxvfCcv0CGV9Mxhp5BVxc0Q/5kMzVC0if+Bbp0wZwYctRandRfFQq20ep8QV99OxIxUcbpq202R5ctQwvzXib796cjco/EFVAEGg0ODVrhenIPpu0quDcXkht3cZY70QBIDw8QaXc6qbjh5AZ6UzoNIYjWw7SomtLAMrXrkBGajrJd20rLZ1el9NfrVKrqNOyHtHXFLuJdxOp0qgaVYM8uZVq4vaF05gsVjZfiiWibICNnZbhARy5rbyskgxZRCZlUMLThbjUTDLNysB+SqaJdfsO4xlYAuHhByo1mkr1sVzPN5TmmrvQTF2uFtZE5QUrUxJRl6wAQgUqNU41amLO7koyX7yIpkRJVEGK/5xbtsK439Z/6hK5/nNq1BhLdBSGP9aS1O8dkvq9w+Eth4jI8VdFMlIziuGvujn+8vBVyn3t9FXUJcpiOrkP1Bo0dZpjPpOnWzIzg/T3u5P+wdukf/A2lpuXMHz9IdbbVzFfOIYqJBTTwW1kfDIMa+wtju86bpdyZbcgJwKPPz0xD1Jai/17WvlPzUraAcwQQrwrpfwGQAhRH9A/SCClvCOEGAeM5+HdROOBTHsVbPSUWRw5cZrk5BRad+rBwLd70vXFtsU69sqOk5RvWYuhu+diMmTxx6jFOfv6b5jBog7v4xHkQ/MhnYi/Gk2/9dMBOLxiC9z9EcPqBbiOnKVMV92zCWtMJM6d3sRy8zLmkwcemrf7nFWg0yN0errd+o60W3fZO3Bhzv4OW6ezoc0EAA6N+5Ym8/qi1jkRs/MUMTuUF03tia/jXbUMSEl61D0OjVmGtFjJXL0AXe+RuM/9CZmehvnAVtRhlZTpk6cOFlkmp1YvoQoogfML3XF+oTsAUZ3mkHjrLiP+/gyTwchvo3N9NHjDDL7I9lHLIZ25ezWaQdk+OvjdFo7+uIt247vjrNfx+oLBgMTz8+VYkxMxbt+A5fZNXN7og/nqRUxH9qPr0AVNjbpgMSPT0kifPxMATZWauLzRR5lZZbWSvmguaffTOL7jGLVb1mPB7kVkGYx8OWpBTtnmbPiM0R2G46x3ZuySCWidtKjUKs7uP82WVUqLZvHYL3lr6ju4BbswMWQfbw8YhNVs4qWqJSnn587C/VeoEuhJRLkAmpTx40DkPbp8twe1EAxrXhEvFycORt5j7u6LKP00kh5Vg5F//4Bz12EgBOaz+5AJMWibdMQaG4nl+im0tVuhLlsLpAWZmU7Wpm8BsFw5hqp0JXS9pgKSzJ17yTqQ/bFhtZC6YB5esz9BqFQYNm7AEnkT1959MF26SNaB/bh06oJTnbpIs+K/lNkzba7v8R1HqdOyLl/sXozRYGThqPl5/DWP0R2G4azXMW7JxBx/ndl/mi2rNgLQrGNz2vXqAID5wlGcGj+HU9N2mA5uxRp7C6cO3bHcuoLl7OGib3xDOlk716IfNRckWM4f5ed5P/DOh/3sUi6UxWHfFl2AYvAUtwSKiyiqL87uGQkRgjJdtS7Ki/0mynTV36WU1bLTCJQB5cGAGtvpqvWklIPz2VwO/PWo6aoOSYzHwyGJ8Xg4JDEen/9lSQzj5b3Fft84V2j2xPn9G/zH1jFIKWMofCpqtTxpJFAzz75d2duXo8jP5rfZ245FdODAgYMn5ymebVRc/s+vfHbgwIEDu/I/0JXkqBgcOHDgwJ48xYPKxeX/RMVgr7GBCcc+tIsdgMbV37SbrZHCvuNEz643PjpRMVlf1X7jAs/st9ucA47OqWI3W0MnX7WbLfnkisk53Jf2G0cB+NDJfl0k3dbab1xgRf1/Lmv0r+BoMThw4MCBg7woIg7/3TgqBgcOHDiwJ3lXdP+X8n+yYngSqeyH8U8kvEd9+B5NWzci02Bk6rAZXDpTcIrh4l/n4xfgS2am0sUz+PURJCUk07XXSwwY+w7urq5Ii5UDQxcRtaHgHHDv6qE0mtcftU5LzI5THJ+0wmZ/pf4dqD25O79W60dWYhrN2zZl4idj0LvpsVqtzJkwj3VrNhaw+9Uv8/AL9MWYXa4hr48iKSGZbn1fpWO357GYLXg5WVFlS2UbNq7H8GNBqWeXjtlS2Q+knm9FItw98Jg8DW3FimRu2ZSj2zN++giat26CwZDJhKEfcuHMpQLl+va3hfgH+uWU693XhpJ4L4mx04bRoKmyztK5tA97j57kowljsUpJ51qh9GlSsYCtzeejWLxHUZCtEOjJrE4NALhzP4MP1h8nLsVAnDaLaqYwek/pR/WWdcgyGPl21JfcOnejgL33vpuAZ4AXarWaK0cusHrSUqTVSt0Ojeg47FWCwksw/aXxNOnSguota5NlyGLZqC8KtTXsuwl4BnijyrG1JNtWYzoOe5Xg8BKM7ziaFl1bPrG0uJOzlmC9M8JJC2YzyT9tJuHrn21suNSvRtCEvjhXDCN6+CxSN+UuoAsY0we3iPqgEqTvOwETv6HvB32p27IeRoORz0fO49rZohccT1w6iaDSQQxuowiJNn2+Kd2Gd6NkeCkMy75A174TqNQYt6/H+LvtPeb0XEd07TohrVbINJC+6JMcVV51mbLo+41E6PVglQA6nnSdlGOMwf5ky2nn166ugSItuxAYKqVckJ32C+Bo9nTWYvFEUtmP4HElvJu2akSpsiXp3OQNqtWpwvhZI+n9fL9C004cPI0Lp2xfgkkJyZw7eZFbPRZQacDzNJz7TqEVQ/1ZfTg8ZgkJx67SYtUYglvW5M5OZZGbPsSHoObVSY/KlUdQqdScP3WJYT3G0K7Ls0z4ZEyhFQPA5EEfceG0bbkunb3Cm+37YjKa2H/2d0wXz5PywSS8v1hM1oF9OcJuUITU8/tjkKYs0pcvRRMWhiY0DIBnWjehTFgp2jd6mRp1qzH54zG80f7tQss1duBkzp26aLNt9uR5OX8f/WM80z74lK9eb0qghwvdl+2kRflgyvnnylFEJqaxbP8llvdqgYeLE4npue+LiX8e5Z2mFWlcNpBBky9RPaIuAWHBTIgYQtna5ek+/V1mdnq/QLkWD5pLZrbKZ/+vRlLv+UYcWbef6Eu3Wdj/E3rO6Et43YoEhAXzfratHtP7MqPT+AK2FuWxNeCrUdR7vjFH1u0j5tItFvafQ7fp71KxXiW7SIuf3n2SVYeWYoq5S2S3MYT9Oo/UHQfJuporlW2OuUvM2Ln4vG0rTupSuzIudapw/QXlpV5mzRy6DniZkNAQ+jXvS8XaFRkwfSCjXhpZ6LVs3K4xmekGm22RlyKZ0XcGg2YOpmrnN0idNBRrQjzusxdhOmIrx561ZxtZW7Ll2Os1Qd97EGkfjQGVGv17E8j4fAaWyGsINw+8vvvzyQdSHiOC29PK06CVZIOU8ncpZa0HP5TKYA+wGbgLvCeEcPqn9p9EKvtRPK6Ed4t2zdjws7KK9uzx87h7uOEbULgqZGE0alE/53jDnURUajW6fOeiy5bdTsiW3b75yx5KtstVJ6k9tScnP/rBRnSsUUR9NvyyGYDoyDsIlQrfgEef/wOO7T+B0WCkau3KWKKjULkrUtmZu3bg9Cip5wfFyMzEfO4MMitXz6xVu+b8+bNSQZ0+dhZ3D3f8HsNfeTmf4UwpLz0lvV0VqewqJdl12TbmwW8nbvBa3bJ4uCi3m4+rDoBr8SlYrJLGZQMBUKOmznMNOPjb3wBcP3EFvbsrnv4FB38zC0g/K9tjr0UTd12JyFihUVUO/LYrjy19sWw9MHYnj62qDavZRVo8vFZ5LIn3Md2OBZOZlPW7cW/d2MaGKfouxks3C34xS4lw1iK0GoSTFqHRUK5aWXb8ugOASycu4erhinch5dLpdXR6txM/LrBtsUddjSL6erTSqr13F2ucIidu2rsDp/r55OvzyLGj0+Wcm6ZWPSw3r2OJVFoqMi0F4Mnf6v8DInpPXYshL0KICsBkoAlKJRYP7APeBL75JzaLksouTOMIcqWyDy3bBKNb/ZMsi8Q/yJ/YmNxVxnF34gkI9iPhbkKBtFM+G4/FYmXHhr9Z+tl3OcdXrlmJF8YOQOWkIenCLfRB3mTmORd9PtntjJhEXLIruRLP1cEQm0jyedvgQAFBfoSUCuan3Svw9vXm2oVrBAT5k1CIMNmkz8ZhtVrYsX43y+bZdlH5B/kh3Nww7tgGgPVePNpKlQvY0HXshL7rq6DRcn/MsCL9FRDsT2x07orxuDt3CQz2514h/vro80lYLVa2/rWTRZ8ts9kXXDKIu6mZBOpytwV6uHAm2vb8IhPTAHjzu11YrZL+zSvTtFwQkYlpuOu0jPjlINHJ6aSrtXgF+pCY575Kik3AK8iH+4XoQg1bMYHQmuGc3XWSYxsKSoy4+3rks5WIV5BvEbYmElYznLO7TnC0EFsevp6FSovn1xICRVo8vFZ5Tu46ZiMtPnHFVJxcnHHSOXG73wcAmGLv4VKzYNdbYRhOXiTj4GnK718FQpC0ch26imW5dydvuRLwDfIlKV+5eozqwe9fr8VoKHymnMZJg/V+7jHWxHjU5QvOOHNu1wnnF19BaLSkTh0OgDq4FCBxm/QxwsOLrL07inU+j8TOs5KEEO2Az1HUIJZIKWfl218a+A7wyk4zTkq5oYChx+CpazE8QAihBb5HkcXI++aaBYwUQqj/meGCm4ovlW1fCpekLliWiYOm8Xqr3rzbaRC1G9bg+Vfa5hy/c+Nu/moyglPT1+BWyr/g8UXIbqtdnKgy9CXOzClETUQIThw6xavNezGmzwRCyoQUWq7Jgz+iW+u36NtpCLUa1qDDy7YaU7Ub1UTl6UnGzw+Xys78cy2Jb3Yjfcli9N16FUzwoFiFXLzCLt3YgVPoHNGdnh37UadRLTq+0t5mf4dObbDeu1WIRLmtHYtVcisxjSU9mjOrcwM+WH+clMwsLFbJidv3GNG6Oqv7tCRTZJGlKtgDUZTazLxe0xnVoC8aJw2VmlQrsL9QjYQijM3r9REjG7yLxklL5UJsFWrsH0iLfzPhKwynLhIy471H2smPtnQwzuGluPJML64064m+cU3cvQq2rPPfY2FVwggODeHg5ofrhhViqMAm46a1pAzqTsbKxei69lQ2qtVoKlUnfd50UicMwanhMwCtHy+zwvK3X4sh+z33JdAeqAK8IYTIX/NNBH6SUtZGUZ5eyBPy1FYMwIfAOSmlTSBkKeUNlIA+3R52cF7Z7cDXatlFKtseqHQeaLxKsHrrMuLj7hEUkqvCGRjsT3xswa/f+Fjlyyoj3UDC3SSGTRlc4PjItQfQ+Xk+UnZbH+KDITYJtzKBuJX2p922mbx4aB76EF86Hf+S9jtmcS8ugcBsuycOncbVVY/RWFCiPm+5Nv++jSq1K+Xsq/9MXZ55rgnmmzchOwKXys8fy8Oknndtx6mpbVeTtnYdnCNa4b1oCfFx8QSVCMzjrwDuxhassB9sy0jPYMNvm6leu6rN/vad2uBvvEdsam6/dVyKAX8326hlge4uRFQIUaSyvVwJ9XXnVmIagR4uVAz0okyj1rh2fI+Vf/5A3N27+OS5r7yDfLkfV7T0s9lo4tS2o9RqUx+AiJ5tmbxhDjElvpsAACAASURBVGWqlyU1MTWfLR+SH2nrSI6tlj3bMXnDHMrWCCc1McUu0uKJsQlIswVdditBG+SH+SF28uL+XBMMJy/h1flZQtfMwalkIEKlwi84b7l8Scx3jpXqVKJc9XIs2beU2b9+TEhYCDN+tBX2M2eZUXnmdkGpfPyRD5FjN+3LjfxnTYjHfP4UMvU+ZBkxHT8IUKdYJ/UwzObi/x5NA+CqlPK6lDILJfTAS/nSSODB4JgnihDgE/FUVgzZ8Z67oojpFcYMYCwPKX9e2e24H0/aRSrbHlgzUzAnR9O9TR92bdxDh1faAVCtThXSUtMKdCOp1Wo8fRTxMrVGjc7FmUUfL6F7mz6cO3Eh5/iK/dpjMWbZdCMBZN5NxpRmwLdOOAChLz9D1OZj3L94m99rDGRdw2GsaziMjJgE1tYZxMZW4zh34nzO13+HV9oipeTG5ZsPLVezZxtz/aIyc6ZCtfKMnz2S97qPRh0YmCP1rItoRdaBh0g9N1SknvNiOnEc464dJPV/h+0bd+d8/deoW4201LQC3UhqtRqv7HJpNGpatGnGlYu5s11Cy5XGw9OdyvosbiWmEZ2crkhln4+iRYVgG1stKwZzJFKpZJIyjEQmpFHSy5Wqwd6kZpqIP/43xr8W0LtjD45uOUCjLi0AKFu7PIbUjAJdP856Xc5YgUqtonrLOsReUxYA7lq5mWkdRhN55jqXDp6jcZeIx7Z1J9vWzpWbmNZhNNdPX+XcgbN2kRa/euoKzhXDMEXHgVaDx/PNSd1etNJuXkwx8ejrVyNpzQZudBmG8cotjv99nFZdla7ZitlS2fm7kTau2kjv+m/yTtO3Gdt1DDE3Ynj/NdtB+Iy0DFR+ATly7Npmrcg6ut8mja0ceyMsdxQ/mU8eRl2mLDg5KxLnVWsBnC/WST0EKS3F/hWDEuSJdAlEUTDK5VSghxAiCtgADHnSc3jqxhiEEN4osrfdpJSphaWRUl4UQpwHXkBpPRSbJ5LKfgSPK+G9b/sBmrZuxNoDa8g0ZPLB8NyvodVbl9G9TR+0Tlq++OFTNBoNKrWKw3uO8vsqJYRkuUphVKtdhUY3l2M1WTg4PDeqWrutM9jURpkVc3TctzSc1w+1zok7O09xZ8fDQ2V7entQtXZl9t7citVsZfb4z3L2rdq6hB5t3kHrpGX+93PQaDSo1SoO7znG2tV/ATB0Un9cXF2Y/tUUQOL99XJkUiKZmxWpZ/2bfTBfVqSedS91wam2IpVtTU0j9eNcH/isXIPQuyK0GpyaNCO6y1CiImPYeOhXMg2ZTHwvdyX6r9tX0rV1T5yctXy9Zj4arRq1Ss2BPUf4ZdUfOek6dH6OjX9spbuninFtazHgh31YrZKXapYh3N+DhX+fp0qwFxEVQmhSNpAD1+/SZfFWVEIwvHU1vLJjNQ9vXY1+3+/J7rVQc3v7Ze61iGP63wvIMmSxfPSXOXlO3jCHaR1G46R3ZvCSsWiypZ8v7j/L36uV+6p22wa8MbUPbj4eBJcrgclkYsbfXyhTX0cvLGDLWe/M4CXj0DppEWoVF/efyWfrbdx9PCgRXgpTlumJpcVVajXWtAzUbq6U27SY5F+2kHX1Fn7v9SDzzBXSdhxCV708JRdOQu3hhlvLhvgP7cH1DgNI3bQX18Y1KLt+IUhI232M7+eupv+H/fl6zzfKdNVRuTPGPt84n/faD33oPdqobWP6TeunfJyYMvH4bDnW5ASydmzEevsmutffwnL1Eqaj+3Fu3xltjbpIswWZnkr6F8o9JtPTMK77GY+PF4EE0/GDaGvUXf/QjIvDY4wxCCH6An3zbPpaSpk3PGLRIRhzeQNYLqX8VAjRGFgphKgmnyDgw39Mdru4CCHGo/SZXcm36wegZx6J7prACaDPo6arTi3T3S4n+fRKYpS2my2Az4h6dKJisr7qo9MUl4jT9pTEsN9EgqdXEsO+Kp/T7CiJMcZoT0mMNLvZ8v511xPLYBt2Lin2RXRp+c5D88t+0U+VUrbN/n88gJRyZp4054B2Usrb2f9fBxpJKf+xfv5T12LIPuGZReyenSfdKZ7SrjAHDhz8H8a+s5KOAOWFEGFANMrgcv7x1Vsog+bLhRCVURbpPdFsmaeuYnDgwIGD/2rsuD5BSmkWQgxGWcelBpZJKc8JIaahLO79ExgJfCOEGI7SzdRbPmFXkKNicODAgQN7YmetpOw1CRvybZuc5+/zQNP8xz0JjorBgQMHDuyJQ3b7vwN7xVe254DxgTPf2c3Wvqpj7WYL4O8Vr9jNVve+j57NVVyOzqhvN1uBAx4tilhcYmc8ZzdbonSo3Wxl/bbVbrYABuz2eHSiYvLj6OBHJyom7WYVFFL8p+y2hxFHxeDAgQMHDmx4ijWQioujYnDgwIEDe+JoMfx3oKlWH123gaBSYdq9EeOGNYWnq/cMroOmkPbBQCw3LyNcPdAPmow6rCJZ+zbDpk+BJ4+h8Ervzmi8SiClxJIWD5aC88OLE9tBaF1Qu/rS8OAC7qzezq0Fa233O2mo/MUQ3GuUxZSUyvm+n5GZrfnkWqU0Feb0Q+PmgpSS423HYTWaqPHDBA6bopjx6edYTFl0rluWPm3q2tid89sejlxR1jpkZplJTMtg72xFLvxOYiof/LCduOQ0BKAW3gyYMpA62br7X4yax/VC4gFM+m4q3gHeqDRqLhw+xzcP4gFUDqXfjIHo9DoOndvLjE8+w2q10rlGafo0Kl/AzuaLMSzep3QtVAjwZNaLuQoHaUYTnZfuolX5oJxtH8+ZzHNtI8gwZDKg32hOnTxnY8/NzZVNW3O7nUqEBPHjj38wbsyHNGlan1kfT8KlRmWyNi7FcvU4AKoyVXBq8SoIFeZz+zAf3VygnOryddE2fAGQWO9FkbUpV+hv36UoPl53SIkTUb8CfSJq2Pp/3SGOXI9V/G8yk5iWyd6p3bkYk8CMtQdIyzShVgl6uwra+OpzjtNUr4+u5yDlOdi1AeNfRTwH9ZvjOnQKaZMHYLlhe2/3mvo2tVrWJctgZNGoBdws5FqO/W5STmyHi4cv8O2kr5VYCMBzvTvwXK8O6LwElpvnMO3/nX2RCczZcxmrlHSqEkKfuqEFbG65Eseiw9cRQlDB142ZbQvqQg2dNohGrRpiNBiZOfxjLp/NvxQql5nffkhw6WB6t34HgPCq5Rg5axjAScAMDOQxF8/m4AjUY4sQIk1K6SaECAVuUETsBCHEcqAFkAK4AAeB8VLK6Lx28tjtDdSTUg4WQlQEFqMoCToDe6SUeVcO5ket6zmE9E/GIhPjcZv8JaaT+7HG2CqKonPB+dnOmK9dyNkkTVlk/r4cdYlQVCVDgSePobDpt638uuIPDpz5DuGkR+3qiyUltsCxxYntoHbzw3z/DoefGUvdzTO5t/koGZdzF6cFd2uFOTmNQ42GENCpCWUn9eB8388QahWVvxzKhUELSD8ficbbDatJWZ5/5t1PmRZ4kUWDOlGyRVde7TOAFtXCKJdHb2l0l2dy/v7h71NcjMqdMj1x1Vbeea4ejSuVJsOYxcLfUggOC2FQi35UqF2Rvh8NYFwh8QA+GTQ7R/p59KJxNH6+KfvW7WHg7CEsn76Mc4fOklIqnm+mjMLv1hG6r9hDi/AgyvnlirFFJqax7OAVlndviofOicR0W0XOL/deom6pXA2i59pGUC48lFo1WlG/fi0+m/chrSK62ByTlpZOs8Yv5Pz/994/+PMPZVVw1O0YBvQbw57lk3MPEAKniDcw/v45Mi0J3evjsVw/jUzMlfQWXgFo67Ul8+c5YMwAl9xzsFitzPzjIIvebkugp57uX6yjReXSlAvMld0e/WLDXP/vO8/FGEVjyEWr4cNXn6GMnyd3UzJ4Y87PNPLU4a5RgVChe3Mo6bPHKM/BtIWYjh/AGpMbtwBQnoPnOmO+WlAZolbLOgSFhTCixUDCa1egz0f9mNyp4PjW/EGf5FzLYYvG0Oj5JhxYt5cqjatRr00DxrUbxqKh/uDihsUqmfX3Jb56qTaBbs50/+kILcL8KOeT8/gTmZzBsmM3Wd61Hh46LYkZBXW7GrVqQMmwknRr1osqdSozYuZ79H+xcEWd5u2bkZEvvsOACX1ZPnclc1bNrAV0AD4GIgo18Cj+B7qS/s0FYo+KnTBaSlkTqIiygnlnMeMszAc+y47XUBlY8Ij0Dax3Y5Dxd8BixnR4F9raBWd26Tr3xrjxRzDluemyMrFcOYvMs+1JYyikp+XRhi9cRxN4dGwHoXFGWkxgNSNNZu6u3Ydfu3o2afza1Sf2JyVGQPy6g3g3U76yvCNqkn4+kvTzykvBnJSW0/y9akiglL8XJf29cXJypn2TOuw6U/Cr8AEbj12mXd0KAFy7k4jFaqVxJWUltt7ZiYZtGrErOx7A5Yfo7hcVDyCkbAnOHzqHQWRSykNHaMNWSvyEyiHsumpbof52+hav1Q7FQ/cgfoJzzr7zsckkphtpHOqfs63D88/yw/e/A3DkyEk8PT0IDPKnKMqVC8Xf35f9+44AcOtWNOfOXrRR81QFhiLv30Wm3AOrBfPlI6jL2n7xa6o2w3T6b6VSADDkKr+cvX2PUr7ulPR1R6tR07ZmWXblk0XPy8ZT12lXSwlkVMbfkzJ+ik5UgIceb42aJLNS4avLVcIaF537HBzcibZukwL2dF3fwrg+33OQTd02DdiTfS2vnriMvpixHR5MqX+2Rzv+XPgb5izzg4ScjUuhlKcLJT1dlOtaPpBd121F8H4/F82r1UviodMC4KMv+Jpo1rYpm39RJjqcP34BN0+3QmOIuOh1vNr3ZVZ8vtpmu5QSV/ec1tWTCdFZrcX/PaX8mxVDPLAdJXZCkUiFz4BYFGnZRxEMuZoNUsozj0hfQibmrgy3JsYjvG1f5KrS4ah8AjCfOvTIzIuKoVAYUz4bz+qty3h7uK0LXundGY13KaW1kFa0EuRDUWnAmttkNcYk4hxke17OwT4YoxX70mLFnJqB1scdfblgpIQaayZQd+tsSg3qmHNMsspESHgVdC37IC0m/NVG7t4vXHIgJjGFmMQUGlQoCUBkfBLuLs6MWLKe12b/wNy1e/EJ8uVeTG6LIiE2AZ/AwivSSSum8u3xlRjSDRzIjgdw63Ik9ds0xCTMBJcshXBVXnyB7jruptpKZEQmphGZlM6bq/fSc+Ue9l1XrpNVSj7deZ7hEbZqxSEhQURF5X7JR8fEEhIcRFG8/MqL/Pbrw6V0hJs3MjVXDE6mJSPcbF+ewjsAlVcgzq+MxvnVMajK5JbrbkoGQZ6uOf8Heuq5m5JeaF4xSWnEJKXRoFzBGT5nbsdjlpKSzprsPP2QibnXQXkObO9bVZlwVL7+mE8WLo7nHeRrEyciMTYB78DCAziNWzGZRceXY0g3cGiDIpsdFBZCxQZVmLZ2Ns5dhqMKKMPd9EwC3XMDYwS6OROfr6UXmZzBreQMev9ylF4/H2FfZEEFYr8gP+7muc/i78TjF1TwuXx7zFv8uPhnjAbbe2fBlIUMmNgXFMG6T4CCIfOKi6NieCSPEzvhOFDpkangM2CHEGKjEGK4EKJgaCtbChHxz7tX4PLGAAxrihej+UljKAD8vPx3zEm3sWQkoNYX/OL6pxTU2Sm8rEKtxrNhJS4MnM+JjpPw69AQr2dy+2yt926RuetbhEqNcPMp9JwBNh+7wrO1wlGrlNvIYpGcuBbDiE7NWD3qNaITUjCrCva3FrUo88NeU3m7/ptonbRUb6J8ZX85ej7te3Wg57heoFLZhE0sNH5CUjpLXm/CrBfr8sGmU6RkmvjpxE2alQ0gyMNWVru41/IBXV9+gV9+Wlfk/iLJH/dBpUJ4BWD89VOyNi3FqXVPcHIpMv/C4lAAbD51nWerheb4/wHxKRlM/HE3k8p6o3pwjo+KyyAELt0HYPi+6Oeg8NAehftrVq9pDKyviEBWzY7toNaocfV0ZXKnsZj2/YZTu8LDsubHYpXcum/gm851mNm2GtN2XCDVaDsuV1jZ8vsyvGo5SoSWYM+mfQXSvtTrRb6Y+hVAKWA4sLRYhSsMKYv/e0r5VyuG4sZOyOZR4lUy2+a3QGXgZ5Q+wINCCOf8iR/EY3j22Wen3XHOnX+t8vFHJuf54tDpUZUIxW3cp7jPWYW6XGX0Q6ehDq2Qk0RTuTbaBi3/cQyFTb9to2qtgpHLpDEd4eRaYHuxsJqVVkM2ziE+ZMXa6tkb7yTgXEL5ahJqFRp3PeakNIx3Eri//zymxFSshiwStx3HvXpZALysWmKT08BqwXL3BvFZavw9Ci/jpuOXaVcn10+BXm5ULOlPmdrNcG32BjPmf03c3Tj8QnK7Z5QoXQ+PB3AkTzyA6GvRTOs5hTUzv+fO7VvIVMXXcamZ+LvpbI4NdHchIjwoO36CnlAfN24lpXMqOokfj9+g/aJt3A6sTvepn3Pg0F/cuRNHyZK5X9slQoK4E1v4mpdq1Suh0Wg4efJskWUHkGlJCPfcyl64eSHTbSWzrWnJWK6fAqsVmZKATI5D5a3cU4GersTez20hxN3PwN9DT2FsOnUjpxvpAWmZWQxZvpVBz9WhulvuYyET7yF8cq9Doc9ByTDc3p+L+9zVqMtVQT/8Q3SvvYvbR4tx+2gxSXFJNnEifAqJuJYXk9HEsa1HqPdcAwAS79zjyCalNWKNiwQkAT7exOVp+cWlGfF3tX2cA9x0RIT5KdfVw4VQbz23kg1oqjdH9/p4lm5ZzL3YBALy3Gf+wf4kxNk+l1XrVqFi9fL8eHA1X6z9nFJlS/L5z8qEknavPMffG/Y8SPozShyEf4ajxVAsHhk7IZvawIORX0O+8QYfIKfPRUoZI6VcJqV8CWUGQYEpCg/iMWzbtq16qbByCL8gUGvQNojAdCKPXrshndShXUkd3YPU0T2wXLtAxvzJWG7mzsYwXziB6fDOfxxD4Zk2Tbh2SYlVUCqsZE464aRXxgn+AdJsRKi1oNIgtBoCOjXl3uajNmnubT5K0KtKjAD/FxuRtFd5qSXuPIVrldKoXJwQahVeTaqQfjkKtV5HBZ8QbsUnK1/7niFs2LGbFtXDCuR/My6JFIORmmG5XS9VywSQmpFJ/PnDGA/8yPQxg9m/ZT8R2fEAKhShu6/T63LGHVRqFXVb1s2JB+Dpq/hRjwu3U03c3L1BiZ9wIYYW4bbdPi3LB3HklnKbJGUYiUxKo6SXnpkv1mHTgDZs7P8speLOsHrqezRu+ALr123ljW6dAahfvxYpKanEFRL4B+DlVzryy8+Pbi1Y4yIRXgEID19F479CfSzXT9uksVw7ibpkdoWqc0V4BWC9r5S7akk/biWkEJ2YislsYfOp67SoUqpAPjfj75NiyKJm6dyPFJPZwoiVO3ihTjjP1bC9ZpbrF1EHlUD4Zz8HjVpiOp7vORjYhdQR3Ukd0R3LtfNkfDaJzB+/IW1iP9Im9uPolkM8k30tw2tXwJCaUSC2g3O+2A61WtYhJvtaHt1ymKrZLUHhFQAqDVW9NNy6n0F0ikG5rlfiiAiz7QJqWdafI1FKPkmGLCKTMyjh4YL5zG4y18zk7ef6sWfzPtq+rCw0rFKnMukp6QVC0f6xYh1d6r7Ga426M7jTe9y+HsV7r4wEICEugVqNaz5I2oqC6s7Fx2Iu/u8p5V+frvqo2AlCac8PQRk7eBAq7W+gB7BMCOECvAqMyU7fDtgupTQJIYIAXxTVwaIwG1YvwHXkLGWa3p5NWGMice70JpablzGffHjYQPc5q0CnR2i0rD/WhMFvjCQ6MuYfx1B4tU8XGjxTD41XCNJqxZJWuDJucWI7WNLuofEMosHez7jzw04yLkUROuY1Uk9dI2HzUWK/30GlL4bQ8OACTMlpnO+nxFUw308natFf1N00C5AkbDtB4rbjaP09qb5yHJNizzNw7nysX2+iY92yhAf7snD9QaqUDiAiu2Wx8dhl2tUpb9Mdo1apGN6pGf2+/B0poXIpfy5tu0Bci1gW7l6cPV11fk76TzfMY2SHYTjrdYxfMjEnTsHZ/afZvGojAM06Nqd9rw4AXPj7V/rN+RqrlLxUvRThfu4s3HORKkFeRJQPokmYPwduxtNl6U4lfkJEFbxcip7PsHnzTp5rG8GpMzvJMGQysN+YnH17D/xlMxupc5cOvNylj83xderUYPWar1AH+KAOq45s9AKZq6aRtetHnDsNVaarnt+PTLyDttGLWOMisdw4jTXyPLJ0FXQ9poC0Ytr7G2QqrQSNWsW4jo0YsGyLEieiXnnCA71ZuOU4VUr6EVFFGdjfePI67WqG2fh/y5mbHL8RS3KGkT+PXUXeT2VKmDcVXJ3AasWwYgGuo2fnTNu2Rkfi3KU3lhuXMJ94dPjMkzuOUatlXT7b/RVGg5HFeWI7zNgwl/c7jMBZ78zIJeNzYjuc23+GbauU6bq7ftpOvzmDmb3lc5y9IWvbd2hUKsY2r8jAP05glfBSlWDK+bqx8NA1qgR4EBHmT5PSPhy4lUCX1QdQC8GwJuF4uWhtynZw+yEat2rID/tWYjRkMnPEnJx9S7cs5u3nCp85+ICPR89l6LRBAKeATGxjJDweT3FLoLjYNR5DvumqfxUVOyHfdFU9udNVo7LTl0CZkloSpYtphZTy0+x9c4HnUS4ewBwp5aqHlev+W8/a5SRbbyo8IPk/4WmWxGi4ooXdbNlTEmP15AqPTlRMAof+ZjdbDkmMx2fJqKdUEiN6+5PHY/huXPHjMbw564nz+zewa4vhwdoDKeVN8nTv5I+dIKXs/Qg70SgtjML2jQBGPHlpHThw4OBf4H+gxfB/YuWzAwcOHPzH+B+oGBwR0Bw4cODAjkiLpdi/4iCEaCeEuCSEuCqEGFdEmleFEOeFEOeEEN8/6Tk8dTGf/w1WhfSwy0mq7RiPN9hScGXpP6XpudmPTvQYHKleULLiaUBK+3XHntHqHp2omASZ7PeFaCxizcg/IVZr3+7rakb7xXy+o9Y+OlExqeta9PTnx6XylQ1P7LSMRe8V+0Wh7//5o2I+q4HLQBuUhb1HgDeyg/M8SFMe+AloJaVMEkIEPEm8Z3C0GBw4cODAvkhr8X+PpgFwVUp5XUqZBawBXsqX5l3gSyllEsCTVgrgqBgcOHDgwL5YZfF/j6YEikzHA6Kyt+WlAlBBCLFPCHEwe0r/E+EYfHbgwIEDe/IYg89CiL7Yrpn4Wkr5dd4khRyWv0bRAOVRlCBKAnuEENWklMn5Dywu/8sVgwA+Bzo8v20GB4Z/TeKZmwUS+VQPpfG8fmh0TkTvOMnRSSsBqDGyC+HdIshMVJQv06Pu4VWhBBZDFufmr6XiO+3RursgrZLNHSZhNZrwrh5Ko3n9Ueu0xOw4xfFJK2zyqtS/A7Undyf1Riwa4P6Ri7hVCwOrRJotXJ20nJSTVx87hoLaIwihUgMCqykTa7qtMN/jxHZACEoM7kz0F7/b7nfSUH7+UFxrlMWclMrlfnMxRsUjtBrKfdwP15rlwCq5MWkZKp2WsGl90Pp5ghAIjYpD4T3sZutguZ42tiosGJJtK41L/eZivB2P0KgJnzsA1+phCLWauz//TfSC3ym/YAh+HZvQUEpSoxNwDfDiyKe/cGZpbswEv+qhtJyr3BO3dpxk3xTlnvCtXJpnZr6FZ1gQGp2W1Nv32DFsEeJsJLXmvINXTeVanpm0AlNaJnU+74da50Tc9pOcmajcC1ovV+ovHoq+lD8Zt+M50nc+pvvphA98gfKDXkDj5gJSIrQa/qjWn6xkZeGbUAnabPoIc3omWk9X1Dotd7af4kT2PVZtzMuUaFsXaZUYE1I49N4iSLwPQIfF71G2VS0kkoRL0ax5YVKB69949CtU7toMZ09Xvqr8Ts72Fh/0pFq3VgggKy6JU91nkX45dz2pcNJQ9YtBOffr2b6f59yvAM4lfGm0Zy435vzMra/+osL03gR2boraVUdGbBKXlm3h4hLbeBXFfSZPzvyJmB2ncH2mLoET+yGctGgCfIif+x2JS3PXqbjUr0bQhL44VwwjevgsUvNoJQWM6YNbRH1QCdL3nQDlvfFkg4mPUTFkVwJfPyRJFIp+0wNKUlD5NQo4KKU0ATeEEJdQKoojxS5IPv71riQhRJAQYo0Q4lr2qPkGIUQFIcTZfOmmCiFG5flfI4S4J4SYmS/dC0KIE0KIU9n2ilrS2B7FOeUPjVlKg5m9C03UYNZbHBqzlD+ajsQ9LIiQlrkSyRe+2cSGNhM4OfMnVFoNfzUdyZFxy2j4WT+OjFvGhpZj2f7yR0iTsrS9/qw+HB6zhL+ybQW3zFlijz7Eh6Dm1bGaLewbsIDDzwzHrXpZzvebx9HWo7k4fCEV5/a3iaEQtfgvyk5SXqgPYihcHv01R1qM4GTnKTkxFCypcZiTozEnRynCd/n0lzp1aMOiuR895Cplx3ZIicWcdBu/Ts1wqVDSZn/gG60x30/jRJPBxHz9F2UmKi/nwO7PAnCq1QjOv/YBoVPfpOyMdznffToX3pyp6DflG1C1q61urTEnp3O88RBiFv9F6ETFX74vNkY4aTnZciSn2o4hqFcbAl6LQOvrwYEyb/Dnq9PJSsnAbDByY5OtlEjzGW+xe+xSfnhmJJ5hQZTKDpTTYs473Nh8lPhT19k7eQV3T17jmRm9Ce3RCoCdLcex77WZVJvSg1qz+3By1FK2NR6BW9kgAlop90KFIR2J33OWbU1GEL/nLOWHvAhA6qUokk9d55fQ3pyZ/TOWjMycSgGg/LvtSLkSg2flUhwdvYQNTUbiXjaIoGy7FxeuZ3Pr8Wxp8z4xW09QdYQSVyL8+QaUaV6d71qM4tdXpxcuhAfc2HacNR2n2GwTKkFY69qsbD2GhVWUyqLSnHdt0oR0a4UpOZ0Djd7j9uINhE+ylUWrMO1NErafVK5J61q4Vw8jK/4+27t/jDEpjRJtf/vsQwAAIABJREFUauMeFmhzTHGeyQ1t/h975x0eRdW34Xt2N733SgmQ0EtC76EXqYKiNAUBpUoJIiBFqoBiodgQwYaIYqdJk9577wnpZdOzu8nunu+PWZJsdgMB46vv++W5rlywM2d+e2bm7Jw57X5mE7/3PJJCwn/+OO6Pmov2ym2EVofSy5yrqY9PJn7GSjJ/3W+23SG8Ng4RdbjTazx3eo7Dvn4YyAtv/5oMhrL/PVongVBJkkJMmKDngF9KpPkJ6AAgSZI3ctdS6az8MuhvrRhMuIsfgf1CiOpCiDrALMDv4UcC0BW4DjxrioMkSTbItWtvk5dDOLC/lOP7Al8AIvXMbWzdnHDwNS8wDr7u2Lg4kHr6FgB3vz9EpRKeBgCVujXm7veHALBxdUToDWhTswDIT89BGAX2plhpplj3vj9IcPci57Pw+cO498NhjAUGcmNTZQ+FrQcLPRSUjvYIIZ7IQ8Gckml5IR7H2wEg9edDeHZrapbGo3szkr/bD0Dab0dxaysTMx3Cgsk4JJPPC9KyEEZBQVoWupgksk9cI+WHP5FUynKJlfz9AYtYnt2aFsZK/e0obm3qF14TpaMdKBUo7G0R+XpcW9UtTJt89jZOfu7kxKeRE1fEunL0dcfG2YGkM/J9vPHDIUK6yffIvVoAbpX9uPHDIWIPXMI3vAZ2rk64Nwwh5aD8npOfmoVBo8PO25X00zJuJ+a7gwSY7rN/t8bEfHfwods96oeg1+RjbyqvDgGeBHZqROy2k0gqZVEZ21JUxvQ5RcYzKke7wjLRaEQ3Yg5eJDs+jcSzt7FxtMfR1xJInHj2NnnJ5j0Pfo2qk3E3kayYFIwFBjJP35RbbsXk070JCabymlysvAJ492iCJjqJ3Ov3TWmbknX+Dpmnb5J89Bq2ro6oL9yjUo+i31xZf5MP5BVenfzoeOxqhlAQE4/m0i3sQquYpSmIS0Z3/Z7lYK8QSHY2SDYqJFsbJJUKwDpF8XFUjmMMQgg9MAHYicyS+04IcVmSpAWSJD3g5e8E0kzooX3IXjeWZM/H0N/dYugAFAghCvsvhBDnMB9MKU3PI3cFxQAtTNtckLu/0kyxdEKI0tbDmw3a5MarcfA3R1w7+HuQl1A01a1kmpojuvDU7iUEdmxIvol46VotAL0mn7afTabbzkXUHicv0HYsESsvXo2Dv8yqD+oagSZRjUGbbzZ3WRevxq15bZodeo/6X83k+pQPn8hDAUDp6o/Ks4rcLZVvnd9fqkp4O+QnqLEt6e3g70l+vKmLymDEkJWHytOFvCvRciWiVGBXyRfH0GAMeVqzWCVfU588VppFLNsAT3TFYumz5Vhpvx3DkKej2YVPaXL6I+I+/AUbT1d0xfwEJKWCuCNXzeI5+XuQW+w+5iSocTKVCfX1+3jXr0pOfBrVezXHOdCTnAQ1msQMAro3QVIqcKzsg1u9KhRkFz2otQlqHALkGPY+buhMD2BdcgZ2pgetQ4AHmng1Sgdb/Ds0IPt2QuEx4QuGcX7RJmw9nDFqi6aM5iUUlTGA+q8/Q+9TH1Dl6VZcWvE9AM7+HiBgwObZPPf7QowGg7ytDHL29yA7Xk2D4Z154eA7eLZvQNbZW2Zp5PIqX9Pi5VXhaEfVCX25+/b3xdJ6kHXuNh4tamHr4UxeUjqBHRrgWIzYWtbfZIuVo7F1c8TR3wN9ihqvMQNJWfUNxpw8lC7WabQlpTl3jbxjFwg98hWhR74i9+BpKAJ5PrnKd1YSQohtQogw08v1YtO2uUKIX0z/F0KIqUKIOkKI+kII656tj6G/u2KoB5wuZV91SZLOPfgDXnmwwwTO6wT8BmxCriQQQqiRm1HRkiRtkiRpiCRJVs/h5s2blbt167ZOkqRTe/NMoMSSXHzrgHkAbmzczc8tp/J7l9kY8gsIG9FFPkalwMbVkfPLvmN3vwUEd2+CX5u6pcHqUTrYUmdSXy6u+N7q27wmOokTbSZz6cXlhMwYxJN6KBiyEtGrY+R+eBsHixiPrZLrW6wD70natIf8hDQa7lhOyIIRaO7EP/pNqBxjWb2HQuAcXgMMRk42HMPpZuMIeqU3CocinLPCRom9pwuxh0r4PD3Eo2F/1Ke4BHvTfvkobJzsMZq6EBN3nEITn0bkzkXUXzCMjCsxltfvUS+Hpu8N7BJB6skbCL0BhCCgczi61EzSL9yzWn6Kr0O6+NYWfm0yieitR6gxomvh9XGvFsDPL77NT0OX4VrJB+cA6+Y6peXpwhe72dh2Gsk/H8W1UfVHHiaEoNr0Z4j5+HcMecX5YhLa+yncW/0Lnb99HY+6Vci6kyifa+FXlu03qUnKIGLeEJAk7OvWQP35T4g8rZVjS5dN5QDsalTiZtvh3GwzDEeZrtrusYJYU/nOSvpH9E8OPt8WQjR68EGSpPnF9vUC9gkh8iRJ+gGYI0nSFCGEQQgxSpKk+kBnIAp54ceLpuPGI8/pJTQ09PjOnTv3Apu+ChwqnAI90SSZN5XzEtQ4FvuROAV6okmU01Tu1YwaQ2TEsPr8XXyahhUeY8zXk3UjHoMmn/i95/CoX5V7Pxw2i+UY6IkmMR3nKn44V/ah++6lKGxVqBzt6b5zMee7zTTzUMg8dhX7qv5oY5KxC/JGl6Au1UMBKPRQyDhYfKhGYMzPlXHeBeaetg9VCW8H2wBP8pMsvR1sA73lFoBSgdJVzhfAvXkbCtM13PMOimJEU9sAT4uH5JPH8rKMFZ+GXbFYD66Xz9NtSd93Fr9hXfAb0gmVl6vsTxHoRTZQuUNDjAUG0q+bg3lzE9Q4FbuPzgGe2Lk5MXDHYjl/O08Td+QKKRfuUqVTI5wDPNHEq7k0r4jj2G7HQnkQ2ST7ALksAGhTMrHzdUeXnEHoxD4oHWzpsHsJ6efu4BDoSUDfFsT8dJS6U/ujScwguFdzArs2JqBTIxQOtth6ONF89ViOT/gQxwBPtEmWfgiSSkHt8b3w696YvLQssuPT0Gt06DU6jAUGHDxL71YsrpwENS6BRddCG5+GfSVz61Ndghq7IC+L8uoWUQPfXs2puWwUNm6OICDzzC3sg7xI+GYfZzYfos/BFWgS08m+W9R787Df5IPuW4BbX++jwxfTuPX1Pmz8vfF9bSS+r41E5e0OAjyG9iL9q98een4uXVuhOXe9sELJPXAKx/DaLYADZbpApUhUIDEeqctA40emstTzQGdJku4htzi8MA2ugGznabID7QIMKHbcGqCR6e8nYDggeUdUJz8rD02JPlRNcgb6HC3eEfJbUMjANtzfKTdw7m87VTjIVZCjRVLJl0qXnoNCpaQgOw9JqcC3ZW2ybsShTc6gIEeDV0QNAKoObEvsztNkXrvPjw3G8WvzyfzSZBLCaOTAyJUUZOTg92xkoYeCc/0QFDYqUn479tgeChQzyFPYOsJjejwU93YA8O7bBnUJb4f0nSfxfTYSAK9eLck05UvhYFv4Ju7WrgH6rDxs/Tyxq+SLZKPCu28bszfCvxLLp19ri1jqXacKY3n3aknmYTmWLi4Vtzb1SPx8Bxf7vEFBSgZp204Upq37Yhc0qZkW/ep5yRkU5GrxDZfLRNiANpxd/Qvfd5/Nb0OWcXfnacIGtCFiUl/uH7hIfnYe+uw8eTwD8GlXD6Mmn/z0bDxMZaHys21JNJWrxF1nqPxsW9OFF9xZt4N9nWeRsOMUVZ6PxKdFbTSJ6RRka9AmZ3BxyWZ+bTyR35pN5uiYVRRka7i1XqamVn2mLXE75LjOxQZwCzLziN99jm96zOby5j8JblkbSakgqHktFDZKEk+bdweVpqTzd/AMDcK1kg8KGyVBwzqhuWfus5268xQBpvLq27sF6YcuA3C673yONJ3IwdqjuLtyK7cWfcO993/E/5l22Hi74h1RHb02n4DI+tz7qcgX4mG/yeJjhJV6NCHjeixp5+5gyMohZtjr3O46GmN2Huqvf31kpQBQEJ+CY9N6oFSASolj0/pQHl1J/wMthr8ViWEaND4GrBNCfGra1hQZtb3mAZbbtH0+kIM8uHwLqCSE0Jn2jQDaAK8CTYQQ+03bOwPvFY9T/OuB1UD39Kv3qx2d8gnqC7JZTs8/FrOty2wAPBuE0Oq9MSjtbYnfd56Ts+Xpf60+eAWPulVACHJjU9Gl5+DbvCYGTT4xvx6jSt+WCCGw93blxwbjCmM1f0+eopiw7zynZ1uitfudX4s+V4sKQd7dROwDvLDxdKEgM5cbUz8i+/xtaq2eiEv9kEIPBW20vJDRb0BbKk/qzwMPhTsLv8LGx42WZ1ebmuASxgINxlzzcafi3g5enu5WvR0kGweUzl6ARMyKLcS9/wOVpj9HzvlbpO86hWRnQ+iqSTjVC0GfkcONV95FF5OEXbAPdTbNQQhBfoKa29PW4hBWiZAFIwqnmCqd7THkaknffZqb494rp1hnuDFWjhW2ehJO9aqiz8jh+svvootJRuFoT+j743EMCwYJkr/dR9zaX6i2dBQeHcOxDfbm1+eWknDsGgADdyzm++5ymfBpEEKHlXKZuL/vPIdMU0Lrj+xG3Rc64+Al46dzEtTsn/YJLsmZtNz0Oo7B3qSduMHZqZ9g5+VCxPuvyNNV957nwqwNANh4ONPsk0k4BHmjiUvlxOj3KTDNPmq9ZRbuETXIjUnhxJSPST8vl9eufyxhV5dZ+LSsTf0ZA7F1c5LL2N7znDGVsVbrXsW1egDCKJfX0zPWczdNrvSe2ToXvwbVEMLI+Y1/cGjRJgAGb1/MNz3kc2496zlq9m2Fs587OUkZXP52P8ff3UqvdVOoapqVlZ+g5vyw5fj1bUnW+Tuk7jyNws6GOqsn4FK/KgUZOVx6+f3C8vpAIVEDMeRqifnwN2ouHUnA4A4gSeTGpnJi5gYSD11+ot/k8dfWo0nOoF3PavjNfhlJqaAgNomcA6dQODuivXiTnL3Hsa8fSvDaOShdnTHq8jGkpnOn51hQKPB/c5xcOQjIOXAar5H9/zISI3fBkDI/VJ3mfv2vxG7/7awkSZICgfeQWw5a4B4wGfixlIohFeguhHiu2D5P5BlKNZDHHKoDGiAXeFUIYf56W0IVrKTHUwUr6fFUwUp6fP0vs5Jy5z9f9oph/qZ/ZcXwn3Bwi0d2YCupeiXSzS/2cUOJfWrgQedmz3LMXoUqVKEKla/+xV1EZdX/8srnClWoQhX6z6uM01D/zaqoGCpUoQpVqDxV0WL471Cfp/4yhRaAzr+Xn+fzn188U26xyntMoOnFFY9OVEZNaFJ+ftTvfdC83GK1H/huucXKerd/ucWSXMo2lbQsil9+ptxiAbyeXX7jMhunWK6+flINXFl+YwzbyiFGyZlz/436f1ExVKhCFarQf0wVLYYKVahCFaqQmSrGGP47pKzbBPvnxiIpFOQf3EH+js1W06ki2uI4dg45i8ZjjL6JsnYE9gNeAqUKDHqaZKzh1OGzTFs4iVYdm6PV6FgwZSnXL960iPXh9+/h7eeFTit3P018Lor0tAwGj3mWPoOfwi7AmQMH/mTJsrcxGgz0b1mHkV3MYWErth7k5M1YALT5etQ5eRxaJsNkE9TZbL2exXMjX6HKsT5kfr2PjFXm0MXHwVtnHZUXJlV+fTAqj8qgUKBPu2f1OpUF4/0wDZo3gnodIsjX6NgQtYb7l+9apJm0cTauvu4olUpunrzKpjmfcfjafZb/chSjUdC/WU1GdmxkdsyKX45y8pZMJNYW6FHnaDm08AXi07OZtnE3BqMRvdHI863rFh7z7soF9OjekTyNhpdemsLZc2bQX5ydndi/rwhBHhwUwNffbGVa1DzeWTGf9pGtsA9y4+DJsyx5dxWGjGT61Q1iZJMQi3PadSORj47fQZIgzNuFpd1l4N/4n85wITGT8EB3Vg1px+HbiSzfdQGjEPRvVJWRrWpaxNp5JZaPD8prscL83HirXzNO3kthxR8XCtPcLcjk/fa9aDtzMpJSSdYP28n47DuzOG7Dn8Z1QHeEwYBBnUnKnJXoE+Su14CPFmPXoBbas5dJHD8XgBHzRxPRoTE6jY41Ue9z95IlxHP2xnm4+3qgVCm5euIKn835GKPRSNU6IYxePBZbOxvsAp2QlCowGtBfOoT+lDl6W1mnJbZtBiBy5bUYBef2Ybgs47Jt2jyNsqo8qbHgxDYeINFefvNlmnZoik6jY+W0ldy+dNsibw8097O5+Ff2Z1wXeQ3SsGnDaNG1BcA5IBmZplASb102VbQYHl+SJAlgpRBimulzFOD8YLqqybhiqil5FjBVCHHI5H16ApgihDhgSrsL+FQIseUhX6l0GDyB3HdfR6Sn4jR7FfrzRzEmxJinsnPAtlM/9HeKFj6KnEzyVs1BZKpRBFZl/geLWTJ9BZVCghnQegj1IuowY+lURvYaa/WL545fxNUL5oy/65du8kKPMWxf3YuFyzaz7t3leCWeYcjbm2lfrxrVi+EApj/dtvD/m/48z7XYIs79nG/2sO7LzUgXfufo0F9oun0Fup1n0NyILUxTHG/t1bc1Vd4Yxo1XVprhrW28XKn9zRtc6D4DhEC96yR+Q5ug8iyOgDdXv55dGDygD7MWvv2Qy25d9SLD8Q0JYE7kRELCQxmyeDRv9Ztlke6T8SvRmoihL384jfCezVj64yY+GtMTPzcnhnzwE+3rVqG6XxFgbXqflkXX69AlrpmAeT4ujmyc0AdblZI8XQED3vkepVKia5cOhNYIoVadNjRvFsGa1Utp1aa3WT5ycnJp0rRr4efjx7bz009yT/S06fMBSH+nHws2n2bdwpl4XtzJkM3HaR/iQ3Uv58LjojNyWX/qHhueaYqrvQ3qvKJ1LMMbV0FbYOSHS7EYjIKlO87z0eA2+Lk6MGT9PtqHBlDdx7UoljqH9Ueus2F4e1wdbFHnykiHplV9+G50JwAyNfn0fm8Hbd+YRsKYmegTUwnevIrcfccouFNU9nVXbxM7aCJCq8N1UC+8po0iKWoJABmfb0Gyt8P12acACO/QmICQACa2f4XQ8DBGLxrLrH6W41srxy9HY7p30z6aQYunWnPk14MMnfkCW97/lgsHzrHp0gZEVhq6LW9j//xMDHcuINQJZnH0N05RsN+cB6eoWg+FTyW0Xy8CpQq7Z6JwcN5B3aZ1CaoaxKh2o6gZXpMJiycwpe8Ui7wBtOreCm2uOVfp+4+/58t3vmRbzLZGwCRgLsX4bY8j8T9QMfwT1p464GkTN9xMkiT1Al4G2gghaiHfmG8kSfIXQhiAccAaSZJsJEl6Hhks+LBKAaCZMSUekZoIBj0FJ/9E1aiVRSK7fi+Qv/M7KCj6wRrv30ZkygNbxvh72NnZEtmzHdu+l99uLp25goubM16+ZYSSAaePnEWn0XEpOolK3m5UrlYDG5WSbhFh7L9YOkJ9++kbdG8s85puJ6gJqRGGrT4XocnCrkCQ9vPhJ0Zl6zNzcW4oIwhyztwE8fDBs0dhvB+mhl2bcmyrjGm+e/YmDi5OuPpYDkQ+qBQUKiUqGxWJGclU8nYl2MtVvl6NqrP/cnSp37P93G26m4BvNioltiZcd77eUAie6927G19+LdM/j584g5u7G/7+vqXGrFEjBF8fbw4eOm62/VJSJlWqhhCQdR8bpYJuof7sv5NilubHS3E82yAYV3t5YZenYxEDqnklL5xs5fxdildTydOJYA8nOVadYPbfMH9gbj17l0GNq+Fq4kh5OlkOCv9xNY6BDZuivx+PPjYR9Hpytu/HqWNLs3Tak+cRplat9vxVlH5FP0vN8XMY84qYW027NOPPH/YBcPPsDZxcnXD3tSS1PqgUlKZ794BvJQQ4OjtSo1Eo5GUjMlPlFsONUyirN7SIY00Kr0AMcTfl7hp9PiLlPk0im9Ciawv2/LAHgOtnr+Pk6oSHlbzZO9rTf3R/Nq3aZDXPJjnxV8x6/geQGP9ExaBHxl5Yq85nILPEUwGEEGeAjchwPIQQx4EjwHxgyYPtj1CQUV30IxXpKSjczZHSikrVUXj4oL9wvOSxhVJFtOX65Zt4+3iSFF80yyk5PgVffx+rx8x593W++mMdIycPt9iXnJFLYKUqGFPlh5ufuzPJmTlW48Srs4hXZ9HMZJ4TnZJOUGAAx85fYdCyTWy2S0SbkPbEqGznBtWxDbKop/8Wuft5oi6Gvs5ITMPD33rFOumL2bx9eh3aXC3nj57D373oDdzPzYnkTOt48fj0bOLV2TSrEVi4LTEjh2fe+YHui7/hxciGGAyCoEB/Yu8X9RbExSYQFOhfat6fG9SXLVtKeqRAikFFQFAwxji5dejnbEdKrvkMtuiMPGIy8nhxywmGbz7B4XupFnEAkrO1+LsUAfj8XB1IzjYHIkarc4hW5/DCxv0M+3wfh28nlgzDziuxtPKvhD6xqOzrk1JR+ZZ+n12f7k7ewdJNvzz9vUiLL8p3WmIqnn5eVtPO/mI+6858gTZXw7FtMgtpw4J1DJv1IjM+ewPJ3YeCw3IXnchOR3KyfDlQhUZgP2QOtk+NQXKWH/LGlPsoq9YFlQ3YO6GoVBPvAG+8/b1JSSg619TEVLz9Lc91WNQwtn6yFZ3Gcobh8OnDQe6XGoLcYngy6Q1l//uX6p+oGECG3Q2RJMmtxPa6WGK6T5m2P9BMZKTGN0KIstDArMGKi+2VsB/0CtotpbvrKQKrYD/gJZa+9s5DsczFNXfCIgZ3GsGYfhNp1LwBPQeWYBN5BICtA/q7RVMKrSOHYefpm3RuVAOlQr5dBoPgXlIG9ar483XUIFIU+dxQ5j4xKjv71PX/2BQ7a+dYGpXlg+GLea3ZGFS2KoJqWnZtlUaP2HnuNp0bhBReLwB/d2e2TBvALzMG8evpmygVUil5Kf0t7tln+/Lt5p8s8+FfDWOWuvQTAQxGQUxGHp8+3YSl3euzYM8Vsq0gJoSVF9WS2TQYBTHqHNYNbcdb/Zvx5u9nyNIWtXRTsjXcSsmkmmSLhUrJo3OvjtjVDSXj8++t7pfzYb08WdPi4fMZ0/RFVLY21Gslt1S7Du3BhoWf8ensDzEm3MW2i+ULU+E53rmAZv0stF8vxBhzDdtuLwJgjLmK4e4l7AfNwK7HKIwJdzAarA/2lryX1epUI7BqIEd3HrWa/osVX4Bso/k1sjnOk6mixfBkEkJkIburTSpD8pIerO2ATEogNSwOkqQxkiSd6ty584IEu6JuD8nDB2NGsXnP9g4oAqviFLUC56VfoKxWG8cJC1BUCTWl98Zx2nKEECxbt4DUpDT8Aou6G3wDfUhJsnz7S0mUt+Xlatj5427qhNcq3Ne0bWMC67cg/tblwhkMSRk5+Lg6WcQB2HHmBt0jwgo/+7k7Yy90OLt7olIqiNC7YAj0KBWVDZjjrQ1G7s3bwPkuUVwbsQylqyPau+bdFeWpyGHdeGPbCt7YtoKMJDWexYxZ3P29yEgqfR66XlfA+d2naNS6MYkZRS2qpMzc0q/XuTt0b1TD6r6Ahq1Z/dkXnDy5k/iERIIrFbUqgoIDiE+wbuDVoEEdVCoVZ85etNgX2KA5CffvFeUtR4ePk51ZGl9nOyKr+WKjVBDk5kBVDydiMvIsYvm5OJBYrIWQlKXBx9nBIk1kWKAcy92Jql4uxKiLrs2uq3F0CAtEJKehKtaaVfl5o0+xNPZyaBGOx5jnSZw4DwrMKyunjq2wb1yP4O/Xok5S4xVY9Bbu5e+NOrn0e1egK+DUHydo2lVefxI5oAPHtx9FnZgGwoDCryoAkotH4SBzobS5YJD9LvSXDqLwLXJl05/cjvbrRRhun0dZtR59RvRBnazGJ6DoXL39vUlLMj/XWhG1qFG/Bp8f/py3f3iboJAg3tr8lrWsf4M5tfmxJIQo819ZJElSd0mSrkuSdEuSpNcfkm6gJElCkqTSLe/KqH+qxQAyWO8l5P68B7qCJaY7wrQdSZKcgOVAR8BHkqRSuUlCiE+EEE12795dv1JIdSRvf1CqsGnaHv35Ym8Mmjxypj5Dzszh5MwcjuHOVfJWz8UYfRMcnHCcuBDt16vIfWMEQ7uM4s8dBwvf/utF1CEnK5e0Ej8OpVKJm6fcGFKqlLTp3JI71+SZN2H1Qpm5bBo18+8Rk6QmLi2TAr2BnWdu0L6+5UyWe0npZGl0NAwp6uKoW8WXc+fOI+xdkRxcuGGvo2WvLk+MyhYGo9mgdXlr/5c7WdRzOot6TufcrpO0eFrGNIeEh6LJziMrxfyhYOdoXzjuoFAqqN8hAjuNipjULOLUWfL1Oneb9nUqW3zXveQM+XpVKaq8kzJy0JpMddKvHOeFwYNo0aI7v/yyk2FDBgLQvFkEWZlZJCZaXwz53KC+bLbSWggLq079ho2ISUojLlNDgcHIzpuJRFYz717sUM2Xk7FyOUnX5BOdkUuQq6WhUt1AD2LUOcRl5MqxrsTSPizAPFbNAE5Gy90m6Xk6otNyCHYv+hntuHyfHnUrobt0HZvKQaiC/EClwrlHJLn7jpnFsq1VHZ95k0icMA+DOtMiP7l7j6A9fYnYgeM4uesY7QfI9PvQ8DDysnPJSDb3g7B3tC8cd1AoFUR0aELcbblsqZPV1GlRj1vnbyJ5ByOy1KBQogprguH2efMvdiwabFdWa4jxwcC0JIG9fK6G+JuInAxGR47m6M6jdBogD7zXDK9JbnYu6SXytu2rbQxrOowRrUcQNSCKuLtxvD5Ifs4GVg0snrQPcM3iYpRV5dhiME26WYPsYV8HeF6SpDpW0rkgv2iX3h/+GPrHpqsKIdSSJH2HXDmsN21eDiyTJKm7ECJNkqRGyNPGHix5nYvseXpNkqRxwGZJkvYKIR5m3aTXfrMax8lLkCQF+Yd3YoyPxq7PcAzRN9CfP1bqgbYd+6LwDcKu1xDseg3hq8lGJj4XRVxMPFuPfINWo2PhlKI3jq/+WMfQLqOwsbXhg29WoFKpUCoVnDh4mp++lvk2f3MAAAAgAElEQVTwk+a8goOTA44RPZkzx4Nxb7+HQZNN3xZ1qBHgxdrfj1Gnsi+R9asBpkHniFCzZrxSoeDVPi1ZtGgho8e/yqI/OpG76U80N+6bobKTNu0hdNUkwo+sLsRbA9h4uZnhrW9N/KAwdpU3hsnTVZFQeVTGqMvGmGf+AyuO8e7Ub6hVjHdpurTvDPU7hLPoz1Xka/LZOH1N4b43tq1gUc/p2DraMX7dDFS2NiiUCq4fucThTbt5fUwrxn66HaNR0LdZTWr4e7J25ynqBPsQWVd+o3ww6Fz8et1JzmDlr8eRJLnnY3j7Buw7Gc+27Xvo3r0j168eJk+jYdSoqYXHnDq5y2w20sABvendd5jF+Tw3qC/S3fPMiKzJuJ/PyHmrG0h1L2fWHrtFHV9XIqv50qqKF0dj0nj6yyMoFRKT24Thbho8Hvn9Se6qc9EUGOi5egcDw0MYu+mwHKthFWr4uLL2zyvUCXAnMiyQVtX8OHonmac//gOFJDGlUz3cTX4QcRm5JGZpaFzFm0TDfVKXrCHg4yVISgVZP+6i4HY0HuOHo7t8g7z9x/CaNhrJ0QG/lW8AoE9IJnHifAACN76DbUgwkqMDVXZ/hWH6GpJiklh14CPyNTrWRK0qvA4rtr3L9J5TsHO0Y8a62diY7t2lIxfY9dUOAD6esYYR80ehUCoROg2SnT32w99Ef/kwQp2ATYveGJOjMdy5gE14R5TVGoLRgNDmkb9rg/xFCiX2z0QBIPK16Haux2gwcnLvSZp2aMpnBz9Dp9HxblTRyvZV21cxscfEh5bLEa+PIKh6EMAFIJonnJEElHcXUTPglhDiDoAkSd8i+9lfKZFuIfLzM6o8vvRvx25bfKEk5QghnE3/9wPuAsuLTVcdizyGIIBsYJoQ4oCplvwJaCiE0JjSfgCkCSHefNh3Zo3uWi4nWa5IjM/LD4lx9sV95RYL/n8gMVwqkBiPrfJFYpQ+yP+4GriyLBbyZdO2mL+O3c4c0bnMzxu3z3c/9PskSRqIbEMwyvR5GNBcCDGhWJpw4A0hxABJkvYDUY+yIniU/uMthgeVgun/ScimPcX3fwh8aOW4K0BYiW1lGaOoUIUqVKH/nPRlfw81rdsaU2zTJ0KI4jNhSjfBlo9XAO9SZG9cLvp/sfK5QhWqUIX+U3qcBW6mSqD0KZEQizxT6oGCMV+R7YI8EWe/qfvUH/hFkqQ+f6XVUFExVKhCFapQeap8xxhOAqGSJIUAccBzwOAHO4UQmUDhVLH/2q6kf0LL/iifxVu/140rlzgAQ8bsKrdYUZSfTSKU77jA6lPlZzs6u8nscot1Peyhs50fS0tWlB/2WU35IOIBsoX16bxPqpnG8lvrUm/RiXKLdXlNv3KLVS4qR4aeEEIvSdIEYCegBNYLIS5LkrQAOCWEsFxxWQ76f1ExVKhCFarQf0rlzUoSQmyjhFWEEMLqymwhRGR5fGdFxVChClWoQuUo8RiDz/9WVVQMFapQhSpUnvrvt2P4/1MxPDVvODU7NKJAk88PUR8Rf/me2X4be1ueX/sqnlX8MBqMXNtzhl3LZORv65d60uS5SDyUOoTRiMLRCYQRzfbf0Wz+xiyOfa8+OPTpLy/M0WjIfvdtDDHRSC6uuM5dgE3Nmmh37YBJGwB4af5oIjo0QafRsTrqPe5Y4dvP2TgfD18PFColV09c5lMT37770B68OGckKoUC7b0kLj71OoZilMgn9WNY+kx7HN2cebWuvKDrSf0ThPHRv5An8XboM+8Fapnu5XdRHxJn5V4OXTsZryq+GA2Cq3tOs32ZOb7ZqUsb/N+dQ0F8EugNf8mrgBfeB+QyFlasjCVYyddzxcrY9WJlrGqzWvScOwy/WpVZP/E9ajSrQ90O4RRodHwRtdbimtvY2zJ67VS8TbEu7jnNz8vksugZ5M3Q5WNx9HQhNyOH5JgkajWvg06j45Oo1URbKWPTN87B3dcDhUrB9RNX2TjnU4TRSP/Jg4h8vjPZaVn4OdujsLXBqCsgbdMfJK39wSyGc/M6BM8bhUPtqtwd/zYZJniebZAP1T55HZQKJJWKlA2/w6efMHfJa0R2bo1Wo2X6xHlcvmC52NjGRsX8Za/TonUTjEYj7yxew47f9tC0ZQRzFkdRq04ohuNbMcYW4fIP34xn+bbTsp9FRHVGtqtrFnPF9tOcvCujT7QFBtS5Wg7NKr91Rf8DPj3/KBLDQpIkGSRJOidJ0iVJkn6VJMndtL2qiQGysFhab0mSCiRJWv2ouGGRjfAO8Wdl5FR+mrWOPotHWk138NPfea9TFGuemkmVxmGERcoo4Pgr91jb+w3Sx45C6e2DPuYe6lEvYN+hE8rKVcxi6PbuJn3MCNJfGUXed5twfkUGwIqCfHI3fEbOJ0VLNCI6NCYgJJDx7V/mo5lrGLPIuq/D2+OXMbXHq0zuMgFXLzdaPtUahULBiLkvsSrqfY7XGIrSyZ7Kbww1O664H0P8J79R5Q35QV/cj+HKoDepOv+FQlKbetdJlvadWRijuH/CV7M+Zsji0Vbz+Mn4lSzqMZ03u07FxdOVxk+1sH4zSqhfzy58tHJRmdIC1DLdy+WRU/hh1qf0X/yS1XQHPv2NtztF8f5Tr1O1cU1qRhZhne2c7HEb0g+jLp/UpWuJ6TMa554dsKlmjth44FUQ+/RYcv84hNe0UYX7Mj7fQvLM5YWfwyIb4RXiz7uPKGOHPv2d9ztFsfapmVRuHEaoKV8Z8an8EPURp34+RKW6IfiG+DM/chJfz/qE5xaPshpr96e/sqDTFJY+9RrVG9ekTqRsXPT0rGEc33qA2d2ncvHAWeq3b0RU+/Gsn/kRIxaNsRpr1fi3md1jKjO7TMbVy5XmTxXhuXd+9htzek1HAm4MnMXVjhPw6NsW+1BzsGF+XCrRU99H/dMBs+0Fyelc7z+Da92ncL3PdPzGPU3fZ3pStVplOjbry6ypi1i4wtKTA2D81FGkpajp1LwfXVsN4PgRmbEZH5vAaxPm8csPO8zSG4xGlv52ijXDOrB1wlPsuBjN7WRz1Mf0Ho35blxPvhvXk+ebh9GpduneI08k42P8/Uv1r6oYAI0QopEQoh6gxhyrfQfoVezzM8DlsgSt3bUxZ7ceBOD+2VvYuzjiUsIDoECbz92j8ipzQ4GB+Mv3cDXhoO8evUKBNh9VzdoY4mJRuLiAXo92/15sW7UxiyPyisBokr1D0VIUrRb95YuI/CIKZrMuzdlv4tvfeAhD3hrfvkajUBRKJYd/PYQo0JPy4wG8epo/jJ/Uj6E4u+hJ/RPKSrN/XG+HOl0bc8Z0L2PO3sKhlHt5u9i9jLt8F7diSPKu054ld/8xhFaHITmtXLwKandtzDlTvmJNZcy5DGXMzVTGMmJTSbp2H6MQVGlYneNb5YfrvbM3cbRyzQu0+dwwtfIMBQbuX76Lh+kc/UODuX5Yvr/ewX44u8lrSm+fvYGjqxNuVsqYtkQZKwlEqN6oBrp7ieTHJCEK9KT/chC3rs3M0uTHJqO5Fm3xyiwK9Ih8mVUl2dogKRS069CKH7+TMTHnTl/E1c0FHz/L2YMDB/flw/dlYo4QgnS1XDbj7idw7cpNjCVapZdi06jk6Uywp7Ps21G/Cvuvlc4B234xmu71q5S6/0kkjGX/+7fq31YxFNdRIKjYZw1wtRg5cBDwncVRVuTq50FmfNGUwqxENa7+lj+OB7J3daRWpwhuHzavdxTe3kjOzuSfkDlVxtQUlN6Whdm+Tz88N36D06hXyFn7fqnf4+nvRWp8EUM+LTGtVL79nC/m8/mZL9Hkaji67Qhe/l5kZ2TTtIuMibAL9Ebl5mx2THn4MTypf8LpbaUzqP6K3Pw8yTDLj7rw4WpN9q6O1O4Uwa3DMkAwsG5V3AM80cclmlXSf9WrwKWcyhiAk7sz6cV8D9IT03B/yDk6uDpSv1Njrpkqg7ir0YT3kMtFSP1q2DrY4WzyslAnpuHpZz3W9C/msObM52hyNZzYVgSa7Dy8B+NWTcW2ki9KN3kKbEFCGjb+1suqNdkEeFN71/vUP/EZiR9uxc3dhYS4Ih+JxPgk/APMTZJcXOU8T505nl/2fsPqz5bj7fNwU6zkbA3+bkXTdP1cHUnOsqTYAsRn5BKfnkOzan5lPo8yqaLF8PfIRBTsBJSco/st8JwkScGAgYd4sj7AbkuSdCrLYFkwSkNEKZQKBn0wgaMbdpB+33xOuU39hijc3MjbUqy/2koc7S8/oX5hMLnrPsZxcOnMeet4e+sZWzh8Pi81fQEbWxvqt2oASFw5fpkew3vSYOdyJDtbyz79cvBjeFL/hFqtym+dQIkMWcmP9QwplAoGfzCRwxt2or6fjCRJ9J4zjN8Wf1XqtbGmJ/cqsJ5WoVTwbCllzBTNStZKP8eRH7zKvg3bSTPF2rr4S0Kb12Hhtrdx9nAhKzUTQzHPgtJirRi+kIlNX8LG1oa6Jg+FPV/tYFq7cXy75AuMGh1Bc4p1kT0GZ60gIZWrXV/lcttX8BrYAVs7S6+IkvlSqVQEBvlz+vg5+nQczNlTF5j5pnW7zodlqVSfk4vRdK5b2cy3ozxk1Jf979+qf1vF4CBJ0jkgDfAE/iixfwfQBXge2PywQEIIGyGESgihktLycQssetNw9fckOynd6nH9lo4i9W4iR9ab911Wb10P25at0N+7V8isV3j7YEiz7sQFoNu/B9vW5l1NNuER2EV25J1t76FOUuMdWIRn9vL3Iv0RfPuTJr59WmIqDs4OLBg2jwvdXkN3Pxm9Osv8+5/QjyFyWDds7W3/kn9Cwy5NS03zuFLYu6JyD2LytqVkJaXjbpYfT7JKuZcDlo4m9W4ih9ZvB8DO2R7/sEq8/O1cvGeORenlgf+qN7GrG/qXvArGb1tCdlK6RRkrLV99l44i7W4iR4uVsebDujB+2xIadG5CXmYOHsV8Dzz8vcgsJdbgpS+TfDeRfeuLprk37NYMr8p+SEhcPXYZhVKBJlt+OfL097LAURdXga6AM3+cJKKrfP+yUjMRRiPqhFQM2RqcGsk+JTYBXhQ8pBxYk/cLPam+cQ52VQKQkAgIKgLp+Qf6kZRoboears6Q/Ux+3wvAtp//oG6D2g/9Dj9XBxKLOfslZeXh42KJNwfY8Td0I0FFV9LfIY0QohFQBbClhHWnECIf2eFtGvCD5eFmWgM0Ahpd3XWK8KfbAlApvAa6bA3ZJTwAADpPewY7F0e2LfjSbHtA3Sr0XfISWbOmo/TzQ+HvDyoV9pEdyT962CytMqio98u2eUsMceb9mwVnz6Dbv5dpPSdzYtdxIk18+7DwmuRl51n8aO0d7QvHHRRKBY07NCbudiy3zt8kqHowvpX8kGxt8H2uI0lfmtejT+rHsP/LneRr8/+Sf0Li7fJbJW7UZqHPiOO9njO5vOsUEaZ7WTm8BprsPKv3stu0Z7F3ceDXBV8UbtNma3gzYgxvtZlEdOehiPwCUhZ8gO763b/kVbCm5yyu7DpFI1O+gk1lLKeUMmZvpYwd//IP1vScxYXdp7h3/hbNn24HQNVSrjlA72mDcHBx5PsFG8y2n/7tCG89NYM3ek7D1t6WHJNlbPXwMPKy88gsUcbsHO0Lxx0USgUNOzQm3nT/Hmy/c/4WDjUrobufhGSjwqNPWzL/KNvqZRt/LyR7W1I3buPmoDfQp2ex8/e99H9WHjJs1Lg+2Vk5Vg2v9uw6QIs2cu9xq3bNuHW9dF90gLpBXsSos4lLz5F9Oy5G075WkEW6e6lZZGnzaVjpb7C0FVLZ//6l+o9jtx+mEkjucOBnoDryWMNvQoh6kiTVBZoIITZKkvSi6f8PteGbXXWw6L3gRULbN6RAo2Pr9I+JuyhP/5uwbQmre87C1d+TGcdWk3wrDkO+/GZ4bOMuTm3ez4ivZuFfsxL2WclIjo5I7p6IdDXandvI++YrHF8Yif7GNfKPHsFp3ERswxuDQY8xO4ec1e9hiL4HgOeX3yI5OiHZqFBn5PHmsHn0GN6T8PYRpumqH3D7ouxW+s6295jWczJu3u7MXj+n0Jvg0pELrF+wDqPByMtLxtHpmc4oJMg+dZ3LT88182OQ7GwIXTUJp3ohhX4Mupgk7IJ9zPwYbk9biy5Wflur8sYwHJ9ui5ufB5lJ6RzavAcXT1fqtm9U6J8QfVH+cT7wT3DxdmPCZ6+b+Sd8t3ADRoPxkUiM4t4OXp7uD/V2eIDE6LdgBDXbNyRfo2PL9I+JNeVn8ralvNdzJm7+nsw+toakYvfyyMZdnNhchCd/2VlN8NYPUTg7g0FP1o+7yPhkk5lXQcCnb2EbVhVDivxmXJpXQXZ6Dj/O+JRanSMIM+Vr6/SPiTeVsfHblrDGVMZes1LGTm/eT1CDagz+eAr2bk4U6AqQJMjLzCVfk8+X09cSYzrHmduWs7Tna7j7e7Lk2Eck3oqlwDSw++fGHRzZvJfwHs3p+9pgDEJw/cQVDHoD9drK+fo0ajV3L94GYNG2d3ij5zRcvd2Ytn42KlsVCqWCK0cu8fUC2efg5XcnUaVOCEIIPLU6bDzdAEHa5j0krtpCwLTB5F24ReYfJ3BsWINqn85E6eaM0OVTkJzB1c4TcWnbkOA5IxFCIEkSyRt+p8Nn63hz2eu069gKrUbLa5Pmc/GcPDD/275v6dXhOfk6Bwew8sNFuLo6o05L57WJ84mPS6RBeB0+3LgSNzdXHFQCoc1Bt0Oe8XfwRhwrtpu8MSKqMbp9PdbuuUCdIE8ia8m+6R/uvUC+3sirXRuZlTGHQfP+8tM6sV1kmR+q/gf2/ytrh39txWD6/CvyAPNBTBVDifQvUsaKoTzyNzm0/N6CX75R0u76yRWVX76spI125deQ/Leykl52Lj++0ec5ZR+EfZTUlF/Hc7Yo307sKeXIShqoiSm3WOXJSiqPiiGhTYcyP28CDu37V1YM/6oFbsUrBdPn3sU+WoxmCiE2ABv+3lxVqEIVqlDZ9W8eOyir/lUVQ4UqVKEK/bfLaPhXNgIeSxUVQ4UqVKEKlaOEsaJi+K/QtPDyGRtoe0RbLnEATi0pv+mcZ2bfK7dYUL7eyuU5LrD41OJyi+Uc3L7cYqWOafjoRGWUopSplU+izH2lT0t9Er0V7/voRGXUpXktH52ojBr+Wvl5W28Z9Ndj/IuGbZ9Y/y8qhgpVqEIV+k/pf6HF8G9bx1ChClWoQv/VEkapzH9lkSRJ3SVJui5J0i1Jkl63sn+qJElXJEm6IEnSHkmS/vKqvf8XLQab8GY4vjQRFAp0u39Hu9UclW3XrQ92PUyobK2G3LVvY4yNRuHjj9uqLzDEy1Pr5h64yILXljFz8VTadWqFRqNl9qSFXL143eI7P9+6Fh8/b3QmCNvoQZNQp6YzY8FkmrVujF2AEwdPnmHJylUYMlPo36AyI1uEWsTZeS2ejw/L8cN83Xird0ThPp1vdbLq9yC0k4q8r/YTt/ons2MlWxVhqyaasNs5XH95Jbr7KUgqJTVWjsWpfgiSUknylj+JW/UjDtUDCft4CidiL7HknfcxCujfrjEjGvmYxV3xy1FO3pJpJNoCPeocLYcWvkB8ejbTNu7GYDSiNxp5vrWMOy4PTHb9Hs2w8a6GPiMWoc/Hmp4E4b3ynTfp3r0jeXkaRo2eyrlzl8z2Ozs7sXdP0VrKoKAANm3aStT0Nxk27BmWLpmNoy4T7ByQ7OxBp6Hg6C7yd1vHZ6gatcZh5ExyV0zGeF9es6IIrIr9oAlg74AkSeT/8Q223YeDQoH+1B4KDpjfV1V4JLY9hmHMMq2vOLYd/Sl5dbDdC7NRVgrFEH0N9kVh17wpbpMngFJJ3q+/k/PlJrNYTs89g2PvnmAwYMzIJGPJcgyJSdhGNMJtUtH6UlWVytSf+D5hLetRp0M4+RodX0d9SKwVHPjItVMKceCX9pzm12Xyd/afM5zQlnKZsA9wQHJ0QfNJFIej01hx8AZGIehXJ5CRjataXLddN5P46MQdJEkizMuZpd0skSsj5o8mokNjdBoda6Le564VvPjsjfNw9/VAqVJy9cQVPjMh7KvWCWH04rEA5wA9MA54Iv/R8hx8NuGB1iATH2KBk5Ik/SKEuFIs2Vnkaft5kiSNBZYjs+SeWP9oxSBJUn9gK1BbCHHNtC0UeBeoDWQAWcA8IcQB07qFFcim2A80uMRFKiml45jJZM+fhjEtBdflH5N/4jDG2OjCBLoDu9HtlLFMNk1b4ThiPDkLXwPAkBRH1lQZe7zgiJa2nVpRJaQSPVoMpEHjesxd/hrP97COfp4xbi6Xz5sz5pfNfQ+A44vasGDjEdYtmY3Xtb0M+eIg7Wv4U927iDQarc5h/bGbbBjSGld7W9S5uuIXD2OzvmyYO53kvTEs++lL1LtOma1g9hvcCX1GLmdaTsS7b2uqvjGU6y+/i1fvlki2NpzrMA2Fgy3hB94j9adDaG7Hc7ZzFAtCovlozFNUHjiFgX170S6gPdX9ioBw0/sU9Q9vOnSJayaonY+LIxsn9MFWpSRPV8CAd75nUOTThZjsyuE16L/4JVb3m2NxrQ58+hu3j15BaaNkzNdvUDOyIdf3nwdkTHbrF7tjLHj4GE+/nl0YPKAPsxa+/dB0D9S9Wwdq1AihTt22NGsWzqoPltC2XR+zNDk5uTRr3r3w89Ejv/PTz0Uoi++//5Wh17biNOdj8t6NQmSk4Rj1LvpLxzEm3jf/QjsHbNr1xnCvWJlQKLAfNg3tlysxxt9F4eeLw9glaNcvRGSpsR+7FP3VU4gU8xX0+otHyP/1M4tzKjj4M3pbO1RNu4BCgVvUq6S9Oh1Dcgo+n32E9uAR9PeKyn7BjZukjnwFodPh2L8PruNeJn3uAvLPnCPlRRmxLrm44LflK0DCJ8SfhZGvUjU8lGcXv8TKfm9Y5GHvp79x8+hllDZKJnw9h9qRjbi6/xw/Lixahf72xgEofIIxGAVv/XmdD/uG4+dsx5DvTtI+xJvqnkUz16Mz8lh/+h4bBjTB1d4GdZ7li0F4h8YEhAQwsf0rhIaHMXrRWGb1m26RbuX45YW04mkfzaDFU6058utBhs58gS3vf8vsjfMaAT2RH66RFgHKIFG+K5qbAbeEEHcAJEn6FugLFD7zhBD7iqU/Bpjz959A/3RX0vPAIeA5AEmS7IHfgU+EENWFEI2BiUC1YsdsNqG5H/w9rFIAaGZMiMOYlAB6PfmH9mLbzJxfhKYYKtvu4YN/Hbu345ctMnvnwulLuLi64O37+AucLiWkU6VqCIG5cdgoFXSrHcj+W4lmabZeiGFQeFVc7WXgmKeTXeG+aIUHSfFxhDnoMRToSfnpsExMLSbPbk0Lsdupvx3FrY0MRkMIlI52oFSgsLdF5OsxZMs/ljvKPCp5u1K5Vj1UBbl0a1CV/ZejKU3bz92meyMZ2W2jUmKrUgKQrzcghKB+16blgsn+8+NfeRTL+3ER3r17d+Wrr+XWwIkTZ3F3d8Xfv/QB1hrVq+Lj682hQ8fNtiuqhGFMSUCkJYFBj/7MAVT1Lf0o7J4aSv6eHxDFmEvKWhEY4+9hjJffvBVeARjTEhHpyWDQY7hwGFXtJhaxSpPxziWETr6XNnVqoY+NxxAvl33N7r3Yt21tlj7/zDmETn7hyL98BaWvj0VMh47t0R49QZ3IRpwohgO3hmAv0OZzswQO3BoZVhnWBP2NU1xKyqKSmwPBbg7y7yDUj/13zNEYP16O49n6wbjayws5PR0tAXxNuzTjTxPC/ubZGzi5OuFeRoQ9yP84Ojs+SObGQwCdj9LjsJKKwz5NfyUNM4KA4m8YsZhTp0vqJWD7k+b9gf6xFoMkSc5Aa6ADMkV1PjAEOCqEKKSqCiEuAZesxSijggypRQRLY1oKqjBLEJddj37Y93kWVDZkz51cuF3pG4DrO+sQmlwiZn6Ib4APiXFJhfuTEpLxC/AhNdkSwLbo/TkYDUb++G0fH7273mxfil5FQFAwxgS5O8HPxZ6L8eY8nGi1zLh54etDGI2CV1rXpHU1X4xCsCM6l5ca53PelDY/IQ2XCPOuKNsAT3TFsNv6bBm7nfbbMTy7N6PZhU9RONhxd+4G9Bnyd2VIevzdnVEG1cIQew0/NycuxlgjgEJ8ejbx6mya1Qgs3JaYkcPEz3ZyPy2TyU81x8vPmwvxRwr3P8BkW+MbQREm+5AJMPcAk31171mr6f+KAgP9iY0t+v3HxSUQGOhPYqL18312UF++3/Kr2bZ+/Xpgb9sDCZDcvREZqRgzUlFWqWmWThFcDcndG8Plk9Dx6aLtvoGAwGHsAiRnV4ypcYjMorIkstQoKll2MSrrNseham2MqQnkb9tgdkxhGh9vDElF52JIScG2TukQOqdePdEeO26x3aFzB3I2bcGtx8ASyPM03Pw9rXKcQMaB1+vUmD/Xmz+nPIK8Ubh6YYy9TnKuFj8X+8J9fs52XEoyh0FGZ8gvbi9+fwqjELzcrBqtq5i/jHn6e5FWDFWelpiKp58XGVaAgbO/mE+NRqGc23+aYyaXuQ0L1vHGF/NBfggrgFZWT6oMMj5Gi0EI8QnwyUOSWAtm9Q1JkqShQBPgL0+5+ydbDP2AHUKIG4BakqQIoC7wqLlng0wubw/+HjW/zwrD2DKRbvtPZI4djOaLj3F4RkZlG9PTyBjzLFnTRpG3fg3LP1yASmVZl1qbnjZj3Dz6Rw5hWJ+XiWjRiD7P9DDPlG8VRLba7OCSdGCDURCTnsu651rxVu/GvLnjPFnaAr47e4/a/m442JrnpSTexDoKWuAcXgMMRk42HMPpZuMIeqU3dpV9i10aCaVfdQwJ163m64F2nrtN5wYhZthif3dntkwbwC8zBvHr6ZsYJcuL80SY7L9B1pHipbdKnn2mD5u/+7nw8++//0FYzVbk/7weY2Ya9kOLIaGLx5Ek7PqPRveTZdcPCiXKanXQfqP0hQoAACAASURBVPE2ee/NQBEciuRS4k23RJ70106hWTEOzaooDLcvYDegNCJM2c/PoVtnbGrVJOdrc2ixwssTVbVq6I6fLLU8WZNCqeCFDyZxYMOOQhz4AzXu3Qr9rbNlntdpMApiMjV82j+Cpd3qsWDvVbJ15qTbx8nb4uHzGdP0RVS2NtQz4cW7Du3BhoWfAVQCpgBWblbZJIRU5r8yKNaUpwcKxkprRpKkzsBsoI8QQldy/+Pqn6wYnkf2V8D07/MlE0iS9KPJ5nNrsc0lu5I0JY8zHTtGkqRTnTt3XpDoVMQlUnj5YFSXjsrOP7QHmwddTfoCRHYWdj364TThNVzdXNBptPgHFRl7+AX4klwCFwwUbsvLzWPb1p3UDzf3nQ2o15SE+/cKPydla/FxtjdL4+fiQGQNf2yUCoLcHanq6UxMei7n49L5+dhFzqgNvLv/MkdsM7hRyZb8RPO3I118GnbFsNsqFxm77fN0W9L3nUXoDRSkZpF18jrOpu4gD6EiSWPg/9g77/Aoqvb9f2Z3s8mm9wIhhN6k9x46ghTpKF260puCSPGlKygoIlLFhgiCSu8dDFW6dAikh4SU3SS7c35/TNomG0hgv6/8Xve+rrmSnXnmOWfOlNOec99yQhSkphCZkIyPqxOWsOvCHdpWK51nvzq4GsU6juCL1d8SFRVlFZrs948tRdLYo3bxR9LkHUooKDIpvP88vYvH4ZEEBmb3dooWDSA8PNLieZUrV0Cj0XD+/KWsfXFx8aSlpSHHx0KqAXUxpSxU7t6Ipzm4mOx1qAKCcBw1D6cZq1EHl0M3dDqqYqUR8bGYbl1GJD+F9FTke1dQeWbTUUuunua+APRJYFJ4kIyh+1EVLYklmKKjUftlD42pfXyQY/L2LLS1auDcvw9xU6bloRZ3GzcaVBI+q1eQkIfyPH868F7zhhJ9N4JDOejAM1GjQwNMf58BwNfJgcjE7LmjyKRUfHIMmQL4OjsQUsJbeQ9cdQR7OPIgXo+mchMcen3Aoh1LiIuMwysHVbmXvzdxz6GwP5NBYQ8Q0rUZp3dmiRNtQhnbfyFYOSopFCgjSVIJSZK0KMPuZjo1GYSjX6NUCpa7u4XEP1IxSJLkBTQHVkmSdA+YhDKLfgXICrsRQrwJDEDRZigUhBArhRC19u3bV7lYyVKofBWqbG2j5qSHmlNlqwKyh+zsatZHDlcm+iRXNyWSaedWkhZMJykxiZ1b92a1/qvUfI2kxKQ8w0hqtRp3T6Uy0mjUNG3ViJvXb2cdDy4VROWq1bgfGcuj+BTSTTK7rz2maWl/Mz/NyvgT+kCpxJ6kpHL/SRKB7o7M61CDTxsHUKtSOT7sEkJj4U2zN9oSt8dcYSxuz5ks2m3vN+qTkKFilvooBrdGSlSHytEel5pl0N9UGiElTI48iHnK/fPHFdriC7dpWtFcCxngXlQ8T/WpVC2e/eGJjE/CkG7EdO8C0Tu/of9bPa1Gkz2/0WiEMRVTYkS+UUkFQSaFd526bfn9t930ebsrAHXqVCchITHfYaSePTqZ9RaArPkI+cHfqIqWQI6NALUGTY0mGC/lGJIxpJA89W2SZ71D8qx3MN27gX7lx8gPb2G8dhZVkWCwsweVCpWHnxKd5OELag3qKg0xXj9jlq7kkj2ur65QCznKsnRl+rXraAKLog5Qnn1dy+YYjp0ws9GULY37lPHETZ6G/CTvfVH7+vBk2kyiBwzhrz2h1MlBB27Ihw68/YSeOLg4smX2+jzHfEsGoHNzQo5QIoYq+bnwICGFR0/1yntwM5KQEuZU2M1K+hAaplRAT/Rp3I9PoairDuOlIxh+msekduMI3XOKphkU9mWqlyUlMTnPMJKDo0PWvINKraJGs1o8uq2UXVxUHBXrZUU6NQduWizUAkA2SQXengchhBF4D9gNXAN+FkJckSRptiRJmZESiwBnYFPGKEpugbNC45+aY+gGfCuEGJa5Q5Kkw8DfwAeSJHXMMc/gaMlBIWBM+eYzXGZ8onzk9+/A9PAeut6DMN66TnroCRzadUFTRaHKFklJJC+dB4CmYlV0vQeByQSyzLTJCzi05xg161Vn5+nNGPQGPhzzcVZCm/dvoGuLvmjt7Vj501I0dmrUKjUnj4byy3fZH5V2b7ZGenCZ91u+xohNp5CFoFPlYpT2dmH50etU9HcnpIw/DUr4cPJeNF1WH0QlSYwLqYi7LqO1LGTST/5K0+FTqddfJuaHI+hvhBE0uSdJF24Tt+cMkT/sp+wXo6lxchnG+CRuDFsCQPiaXZT5/F2qH14CEkT9dJCUa8oEs53OnukffsiwmR8im2Q61SlHaX9Plu8+Q8VAH0IqKSHSmZPOObvwd6LiWfz7aSRJ6cX3a1qFSz9cJS6kLlMOf5ZFk52JnDTZLUa9SeStR4zZPhfIS5NdEOSk8G7Ruc8zKbwBdu46QNu2zbl29RgpKXqGDJ2QdezP07vMopG6dXuDTp36m53/7rsDeaN9KxzdtIjEeCSdM07TviL91F7kiAdo272N6cFNTJefEfWoTybt4FYcJy4GAaZbF5CP/4HDgGkgqTCeO4iICsOuRU/kR7cxXT+Dpn47NOVrIWQT6JNI3fxlljuHIbNR+RQFrQN+m38ieevveC1ZCGoVKX/sxHj3Hi6DB5J2/Qapx07g9u5wJJ0Oz//MBMAUGUncFCXSSO3vh9rPh7TzykzW1YPnqdSsOh8d/pw0fRrfT/oqK93JOxawsN0U3P09aTOqCxG3HjFp+3wAjq7fzcmNSjhtzY4NOff7CTKnwDUqFVOalGPktvPIAjpVDKCUlzPLT9+moq8rISV8aBDkyckHsXT5/iRqSWJsg9K468wZhc8dOEv1ZrVYdmQFafpUvpy4LOvYoh1LmNRuHPaO9kxZNQ27HBT2e75T5rK+nvIlA2cOBrgIGIDck8AFRmHmGAoCIcQOYEeufR/l+L+lVRPkH6LdliTpEDBfCLErx77RKCGqnwOLgfJAJJAILBRC7MsnXHWkEMK8GZQLcW82tcpFWpcSo7HVfFmbEqPGyrwRNS+KGaPPWs2XjRKjcEg4mP+Q6YvAmpQY8ydYj6q8/yfWo8PfdH/bS3/VL5XoUODvTeW7v7+Sy6T/kR6DECLEwr6lOX62y+e8ddhotm2wwYZXGDauJBtssMEGG8xg7aGkfwK2isEGG2ywwYqw8srnfwT/ioph2Dn35xsVAGcWVbSKHwC/ERufb1RALPR84bU4FtG02xKr+bpRNi+nzYvCmvMCSWGHreYrpOpgq/nSy5YXi70IWtoXe75RITAtONxqvlrNzxvi/aL4qcir9SE2/Q+wq/4rKgYbbLDBhv8WbD0GG2ywwQYbzGCbY7DBBhtssMEM/wNBSf+eisEaXO32wS4cPXGKOfMXIBvTebNaMIMalMvjZ/fVML4+eg2Asn5uzO+srK4PT0hh1vZzRD7V4+2n4UmMkXnzP6J1mxBS9AZGDJvExQtXzHw5Ozuxa2/2fETRIv5s3LiN9yd/TIOGtdnw/XK8vT1JehTL7iGfEXP5Xp78eFcOptniYWgctDw4cIHjMzYA4FUhiMbzBmLn5EDiw2j2j/6K9CQ9dnZ2nD2zh1Ilg5FlmXHjprNqjbmGhbOzE4cO/pr1O7BoAN//sIUJE2fw6aKZNA1R5j2C/H3ReHthfBTB0807iV/9s5kft35dcO3aFmEyYYpLIHr6YozhyurjgBVzsK9SHsP5K0S8q6znsYZ+wuPHEWjci2LSP0WkJuYpL3gxbYexs9+jfvO6GPQG5oxbyN+X8188u2DtfygSFEDfFgple+mKJZk0fxz2jg6EP4wgKiKauo1rYdAbmDF2Ltcv/Z3Hx8rNy/D29crS/BjZaxxPYuPp2q8TPQZ0wUmoSU028CQsmqDqZV5aD8Pvq3GYIiIQJhP67dtJ+cH8mXDs3h1d+/YIkwk5Pp6nCxciRyoUI85Dh2JfX6FrT/r2W7hpPsdTkLJbtmkx3n7Z1zu292TiY+NxqF8b9wnvgkpF8rYdJK43z7vzW91w7tQuK19xsxdhyljhHnhqD+m3FWZbUz6r3gsLW4/BipAkyQRcAuxQhDLWA58JIWRJkkKAiUKINyRJ8kMhuCqWYXtPCGFx3UMmrMXVPqaZntnfHGT1ssV4XvyNt9ccpGmZAEr5uGb5uB+XxJoTN1jXrymuOi1xydmL4j787QyDG5ajfkk//EdupFXrEEqVDqZalebUrl2NJZ99TPOQLmZ5SkpKplH9N7J+Hz62jd8y9ABKlAji1s27xB2+SvytxzSeO4BfO87Mc11N5g7kyJTVRJ67RbtvJ1EspAoPD/1F00WDOfmfHwg/dZ1yPZtQbXh7Qj/5hcWfzsTVxQUnlxK0adOMn39ayeq1P5oRsCUlJVOrduus36dP7WTrVmVx5oRJSh5UKhX68Msk7TtG1JQFBG5cRvLBU6TfeZB1Xuq124T1HIUwpOLa8w28JgwmcqKy+jl+7SYkB3tce7QHrKefMHbc9OdOPhdW26F+87oElihKz0Z9qVSjAhPnjWVoh3ct2jZ9vTEpyeYUX+8vmsgXH6/g5IkzTJg1miatGtCpQS8q16jEB/Mn0r+95YW4096bxbWL5kJRu7bsZfO322hpX4xW47pRv28rZtcY9tJ6GCItjafLlpF2+jSeK1aQevw4pvs5tB1u3iRl2DBITUXXsSMuw4aRMHs22nr10JQtS+zgwWBnh+fnn+P4QygpSSmFLrtZ783h+l/ZlaRKpcJj8mii3puMKTIav/XL0R85ifFujnzduEVkvxGI1FScunbAffRQYqf+BwCRmkbk21kEDBQL3W8x3cLA9D9QMfzTegw5oc8gxauEolbUDphhwW42sFcIUVUIURHII3WXG9biar/8OI4gXy8CPZwU7viKgRz62zxSY8v5u/SsWRJXXaaGgkKMdzv6KSZZUL+kX5bPdu1b8uMPSqs7NPQCbm6u+Pnn5cPPRKlSwfj4eHHiuMKJVLtOdb5ZuQGEIOFuBPauTjj6mkdgOfq6Y+esI/KcQu/99+ZjlGij8Pu7lwwg/JQiGhN25DIlXlf0HJo0rs9vv+8GYPdupdzatA7JN1+lS5fA18ebo7l0CurUrg5qNYm/7ASjkaSdh3Bqbi4Cbwi9iMhoARouXkPtl82Toz99ATkl+wNqLf2EgqCw2g6N2jRg1y97Abhy7houbs54+eal+NI5OtBzaDfWf27OGBtUqhgXTv0FgIeXO9oMDY5L567g4upcKM2P5KRsfZHgWuVIiFDI5F5GD+PqvrMIgwE5JgaMRgwHDmDf0FzbIf3CBcjQdki/ehWVj/Isa4oXJ/3iRYVaxmDAeOsW9Zpla4cUtOwsoUL18qQ/fITpkaI5kbL3ILqm5lF6qWdzaE5cumZRc8KaEEgF3l5VvEoVQxYyGAKHAu9Jefl0A1CoaDNt/3qev/y42i1h2rczWXXuWwzJejOu9r5TB/CkUhuKlK2E8Zzy0fRz1RGVaN7yux+XxP24JPqvP0TftQc5fjsia7+Lgx3jfzlFz1X7cXFTZegBZFcsjx5HUCTAnEgvJ7p178CWzduzfuc+Pyk8Did/8wrPyd+D5PA4izZxNx4S3FrhLCz1Rl2ciygvo0mWqVChDGq1muDgYmi1Wiq9Vj7ffPXq2YlNm/LydlWtWhHJToP+9AUAjJExaHy989hlwrVLW1KOhuZ7PD/9hPyQn37CmdA9qF18QaXO99zCwsffm6jH2UMRUeHR+PjnvdYhkwfx09ebMOjN6VXu3LhHo9bKB61c5TK4umX3QqPCo/AJsFxuM5dM5ce9axk8zpzHqceALkw5/BnBNcty6Kvse5Oph5EfMvUwbmUQLmbqYTwJizYTGJKjo1H75P+B1bVvT9qfCkeU8fZttHXqgL09kpsbdtWr41sku0IvaNkBTF08mXV7VjJgbJ+sc02R2aGvpsho1D75P2NOnV7HcCKbu0rSavFbvxzfNcvQNW2Y73mFgSwKvr2qeCUrBoAMKTsVkLtJ+CWwWpKkg5IkTZMkqUjes82VkfQmC8zcL8DVnnZqK3LMQ+wadM2Rjvn5JlnwIC6JVX2aMP/NOszafo6nhjRMsuD8wxjGt6jM94OaoVZLqDWF0wPo2u0Nfvk5+0NXID2BZ9gcmvgNlfq3ouv2j7FzckBOV6icH4U9JiY6ltOndrL401kkJDzFaDTmm68ePTrx08atefY3aFAb46NIkOWciVv04fxGc+wrlSF+rWWtZOVSrKOfUKt2a0S6HrWz9bh/CpK3MpVKUTS4KEd2HctjO3f8QroO6Mz3u1ejUWvylreFy5z27ix6Nu/PO51HUr1uVdp3zx5C+3ndFhY0HUvU7cfU7NrkmfnKxDP1MAqhd+DQqhWacuVI/kkZ6087c0YZfvryS9ymTyf9yhVMRlOWfUHv66xRc+nXcjAj3xxD1TpVaNutVaF0GBxfb4m2Qlmebsie53rcoTeR/UcSO30u7uNHApSyeHIhICMVeHtV8cpWDBnIU3JCiN0oUp/foBDtnZckKU/TRQhhJ4TQCCE0hliDVbja/Vx0hD9+hMorEIDIp3p8nM1Jz/xcdISULZKhoeBEsJcLD+KS8HPVUc7PneL1WuDUcQw7dm4jOiqKwMCArHOLFvEnPMKyHsBrlcuj0WioXac6x07+wbGTfxAeHml2vnOAJymR5gukksPjcArwtGgTfzuc7W8vYHP76UgqCbWDlm675vDocQRbf9tFrdqt6dJ1EE5Ojpw7Z7ljVqVKRTQaDedy6BRkolatamZDQRo/b4zRefUAdPWq4zG0NxGjZuTRA3Bq3gCHmq8R+Mtyq+knAMiGRCSNvcVzC4pMbYd1e1YSExFr1gr2DfAhJtL8WivVrET5ymX45dQPfLV1KcVKBrJs02IAajWqgYe3OyqVihtXbhIfF5/Dly/REXkJ8TL3pSTr2bVlL69VU9TZegzowo971zJ2xzweXbpDyTrZqm0vqofRaWZ/VB4euM+Zg6ZcOVQ+Pphi8uZJW7MmTn36ED91qtm9TP7uO+IGDyZ+4kSQJIJKFWPdnpUFLjuAmBzXu3frfipWq0BUeDRqv+zXX+3ng8mC5oR9nRq4DnyLmAnTzfKVqU9hehRO6rmLANUtFk4hYBtK+j+EJEklAROQJ1RACBEnhPhBCNEXRciiSW4blJ5FNaCatbjaKxXx4EFCKg9vXFa446+G0bRsgJmfZuUCCL2vdG2fpKRyPzaJQHcnKgV4kGhIJ/rcYVL/WMbrbTuxY/teer/1JgC1a1fj6dNEIi2I/gB0696RXzb9zjcrN9Co/hs0qv8G23/PPt+thD9piSmkRJlXDClR8aQnG/CtrjSEynZtxL09CuOpg5drZmHjUsyHY9PX80vbaezadYAB/XoC8N67AzEajRw9anmcvlfPTmy00FsoW7YU9lotag83NEX9QKPB+fUQkg+eMrPTli+Fz4zRRLw3A1NcQh4/yQdOYDh7mbBuI62mnwAgaR0RphfXdYBsbYcBrYdyZPcx2nZrBUClGhVIeppMbK7Gx9Zvf6NTzR50q/cWIzqP5uGdMEZ1Hw/AgT8OM6D1UN5qPQh3DzcMemVMvHKNSgXS/GjcqgG3biiRdicP/0nvVgP5rN0HJEQ+Qc5onb+MHsbc+u9BejpPFy/GePs2Ds2bk3oil7ZD6dK4jB9P/NSpiPgcaahUSK7Ks6YpWRK7UqX4bPoyBrQeWuCyU6tVuHkoPtQaNQ1a1uPOjbtcv3Adu6CiqIsomhOOrZqhP2KeL7uypfH8YBwxE6abaU5ILs5gp9B3q9xc0VapBPA8DfnnQi7E9qrilYlKyomMHsAK4AshhMjZXZQkqTlwSgiRIkmSC0rX74FlTwqsxdXuVNSJ6Z61eWf4SGSjkU5Vi1Pax5Xlh69SMcCdkLJFaFDSj5N3oujy9V5FQ6HFa7g7Ki3TcS1eY9gPR7N6ur9tO0DTpk25eOkgKXoDI4dNzsrXsZN/mEUjvdmlHd26DDK7rujoWOo3qI2Tow4hBIkPs1tw3XbN4Ze20wA4OnUtzRYPRe2g5eHBizw4qESblOlUn0r9FSr3uzvPcGOjIvR+/sJlatWuRkrSXdLS0nm7z8gsv2dC95hFI3Xr2oEOnfrmKfNePTvx86Zt9L0TQcDXc5HUKp7+uof02/fxeLcfqVf+JuXQKbwmDEFy1OG3WNEAMIZHETFqJgBF1n+KtkQgkqOO4vu+wzh4HHfvPnhp/QSj0YTKwQ1TUv60DIXVdji5/zT1m9fl5+PfYdAbmDt+YdaxdXtWMqD1s+n9W3VuTpcBnRACDuw4jJOzI9tObsSgNzBz3Nwsux/3rqV3q4HYae348sfFaDRqVGo1p4+e4dfvlGHGnoO6UrdxLXQmCX1CMtcPXXhpPQzZJGMMC8N1zBiE0Yhh505M9+7hNHAgxhs3SD1xAucRI5B0OtxmzVLOiYwkfto00GjwXKqQJ8spKSTMmYPJlP1ZLEjZ2Wm1LP5hIRqNGrVaTejRs/z2/XZkWebJwmX4LF2ApFaR9NtOjHfu4zpsAGnXbmA4chL3MUORdDq85ishz6aIKGImTMeuRBAeH4xTBvtVEonrf8Jz+sSXrhhMVu4JSJLUFkWOQA2sEkLMz3XcHvgWqAnEAj2FEPdeKs1/Qo/BEiyEq24AFlsIV50EDMywUQFrhRCfPst39+KdrHKR33787+BKei+ycAI5z4I1uZIq3nrpdzYLry5X0sv1YnLC2lxJE6zIldTlpvUGK6zJlVQsdP9LO9vh16vA35t2kT89Mz1JktQoAmatUIJuQoHeQoirOWxGAlWEEMMlSeoFvCmE6PlCmc/AK9NjEELkGyIihDgEHMr4fxGKWI8NNthgwysHK88d1AFuZQTjIEnST0AnzIe8OgEzM/7/BfhCkiRJvESr/5WdY7DBBhts+P8RslTwrQAoCjzM8TssY59FmwyN6ATgpSTybBWDDTbYYIMVUZhw1Zxh9Rlb7skoS9VH7p5AQWwKhVdmKOn/Eus/CLaKn9Ef3bKKH4CIua2fb1RA7Jn31Gq+AJ4uedNqvuYuyj8suLCwprayNecFDl1cZTVfctzj5xsVEOnfPHPqrdDo8pOD1Xzt7uNoNV8DfzI936iA2GQFH4XJjRBiJbDyGSZhKPQ/mQgEcj8kmTZhkiRpADfgpV48W4/BBhtssMGKkCWpwFsBEAqUkSSphCRJWqAXkJtm4DcgMwSvG3DgZeYX4F/SY7DBBhts+G/BmnGeQgijJEnvAbtRwlXXCCGuSJI0GzgjhPgNhVR0gyRJt1B6Cr1eNt1/RcVw/F40iw5dQ5ah82uBDKpTMo/NnhvhrDh1CwmJsj4uzGtXlcdP9Uz8/TwmITCaBCqVG0VkL3rNGEjlZjVI06eyduKXPLhyN4+/Meun4ebrjlqt5mboNb6fvhohy9RsV4+OY3ugK1OU1J/mI0cpSzBUxSuibdoDJBXGK8cxntmdx6e6TE3s6r6B5OgCag3iaQype9YDV/LYulUpQY3Ph6F20BK5/wKXPlQWLtm5O1H769E4FvMh5WE0oUOXkp6QTOmRb1CsixL2Gnr/AnOXfoUpPprOFQMYVKsESBIO3ScjkhNI3b6CPX9HsOL0HSQJynq7MK+tQh/y7tZz/BWRQPUi7iztqCwibT+jH2WbVSNdn8bmiSsIt0D73Gv5GDyL+yGbZG7sP8eeDNrn4DrlafdRX/zKB2Hc/wt21RqCSkX6yT2k7bNMn6Gp1hDdoA9IXjQW+aEy/KcqEoxDz/fAQQdCoP1jGGmp6Vahyta4ByLkdEyJURbpGApL4X3s7CUWfPMjsizo0qox73Q3Jw9+HBXDR5+v5cnTJNycnZg7YTD+3srq9uEzlnDpxm2qVyjDkiKgLlcd+47vKGX25z7SD26xmKa6cn10/SaT8vlE5LDboNZg33U4qsDSIGTStq0GzjBy1ghqN69Nqj6VT8Z/yq3L+Q+vzlozk4Agf4a2HG62v9uwrjh/OAQ5Rgl/TQ/dR/qhXy25UPLVZxIpSychP8rIV5fhqIqWAiFI+301oKzKtwa1PnABJRR+JPBnHgcFgLUXrgkhdgA7cu37KMf/BqC7NdP8R4aSJEkySZJ0QZKky5Ik/S5Jknuu4+MkSTJIkuSWY1+IJEkJkiSdlyTphiRJRyRJeiOvd3OUK1dOPf/AVb7oXIvN/Rux60Y4t2OTzGzuP0lmTegd1vWsx+b+jZgUohDG+TjZs65nPTb2aciG3vV4qImiXEgVfEsEMC1kFBumfs3bc4ZYTPfrdxcz+/VJzGg9HmdPV2q1rwfAoxsPWT78E+RHOV4oSUIb0pvUrV9g2DALTdnaSJ7mK6old1/sarUh7fQfyJH30K+bTtr+79E2f8ti+tUWDOLCxNXsqz8e55L++DZXxufLjupI9NHL7GswnuijlykzqgMAt5b/wcGWU9nf8gNmz5nL1x9PZfPb9dj1dwS3Y5PQVGmG/EShn7gfn8yaM/dY1702m/s0YFKTbE2KfjWL85/W2WsXyoZUw6uEP0tCxrN16io6zjFfpJeJY99s5/MWE1ne/gOCapalTIiS3/jHMWyeuIK/tp3Arn5rUlbMIHnuSDQ1m6LytxCnb6/DrkkHTPeuZ+9TqXDoOwHDxi9JmfcuKUs/wJhuMqN7XjhlMRPnjbWYN8ifKvurud9gjA9DTk1BpbOsLd65XStWLP5Pvr5zwmSSmbvie76aOY6tX37MziOnuf3AfEj50zU/06F5AzYvm8WwXh1Yuj5bf2JAlzbMGZ8xfyKpsH9zKPrVH5PyyWg01Roh+QbmTdTeAW2j9pjuZ9N329VVViLrF4/FsHIW2g4DqdO8DkVLFGFg40F8NuVzRs99L9/raNi2IfrkvBxlPgHe1GhcQ9F0+P5TUhaPQVO1seV8aR3QNmiH6UE2zbZdHWVBpv6zcRhWzULbFDJ5RgAAIABJREFUfgCSJJlR63/9wZcM+c8Ii/la/O5CJr0+lvGtRuHq5Uq99gpxXia1PgpbwkfAQosOCgArRyX9I/in5hgyKbZfQ+n65CZf740ytpZ7FvSoEKK6EKIcMBolXrfFc9KqU8zdkUB3R4Uqu5w/h26b8+v8eimMHlWDcHVQlsd7ZqxUtlOr0GqUIkrLWKlZo3UdTm1RFkfdOX8TRxcn3HzyfhAMuSi8MxuSEbcfEXnH/EVX+QUjEqIQT2NANmH8OxR1ySpmNppKjUj/6zDqYuUwXjsF+kTkiLtI9jrsc1Ft2/u6o3HW8eSs0vp98PNRAtoqVNv+bWry4OejefZn4qE6maCgIAKSHynlVcafw2GJqIMrYbyqUA38evkRPaoE5igvbdb5dYt54aTNXpJSoXVNLmxR0gs7fwsHF0ecLdA+381B+/z4yr0sBtD4sBgirz/E0cMZ8fQJIjYSTEaM546gqVwvT7nbt+9D2v7NZkyg6vI1kB/fQ36c0bNLSUSWZatSZYv0FFRapzznQuEovC/fvENQgC+B/j7Y2Wlo26QOB0+fN7O58yCculUV/qM6VcpzMIO9FqBe1Yo46ZRJYlVQGeSYcERcRpldOIamUp08aWrbvEXaoa1gzC4zya8YplsKz5RITkDok2nbuw17Nyt6BdfPX8fJ1RlPC+Xl4OhA1yFd+GHpj3mODZ8xjP1b9oNsRMRHK/m6eAxNxXzydXgrpGcv+pN8i2G69Vd2vgzJlKpS2mrU+hlwI+8Eb4FhI9GzDk6SIy5XkqRSgDPwIUoFYRFCiAso2gz5N1sUFPVzySa683N2IDop1czgfnwyD56kMOCnU/T78STH72VTJUQk6umx4RivrzpEMaMP3n7exD3O5q15EhGLez40xmO/ncanZ1dhSDZwdscpizYAkrMHIjGbu0kkxSM5mz/UkocvKnc/NGVqoqn9OqriFbNsdQHmtroAD/Q5qLYN4XFZNg4+bqRm8CmlRsVj7+1mdm6ivaBIcClMty9klJc9MS5FSDuxNesluh+fwoP4FAZs+pN+G//k+L28ZGqZcPHzIOFxdl6eRsTh6p/3hc2Eg6sj5VvU4PZx8+ExO50WkZwdfSXHxyC5mYdqqwJLIrl7Y7piTt2t8i0CCHQjZuM46TO0LRS+JWtSZau0zqB6+ZHZyNh4/Lyznyc/Lw+iYs25jcqWKMa+Ewrf1f6T50jWG4h/at4LBpBcPRHx2fdGJMTmLbMiJVC5e2O6dsZsv/z4rvKxVqmQPHxRB5bCt4gP0Y+z342Y8Gi8/POGyw+Y1I/N32wmVW/+ntVrVY+YiFjSDGmQgxJDyZf5O6QqUgKVmxem62fN8xV+zzxfRUvhVcTbatT6KOsBPgE+sHhyAWCSCr69qvhHK4aM5d4tMJ9l7w38CBwFykmS9Cxu5HMoDKvPTOZ5e0yy4EF8Mt90r8O8dlWZvfcyiQal9eTvouPnvo3YNrAJkeonyFLeMeT85v8/6zeHiXWGotFqKN+gkNQQuZxKKhWSuy9yxF2Mp7ejbdEXtDrL6VukIi5Ysu5VSyBSEiFVEXuRvAORTOmI6Ow1Nkp5pfBNl1rMa1uZ2fuvkpiabtGfZVpky2mr1Cp6LH2Pk+t28eRhAWQWc164JGH/5hBSt6625Bh1yYoYvv2ElM+moKlSn5qNqluNKlvjXjSjzK0w7WjhYcqdzQmDunP28t/0GDOTM5dv4OvlgVpt4VV+HiW1JGHfcRCpv6/NY2YM3Y+cEINuzCfYd3rHfGjuGfktWbEkRYoX4fgucyI7ewd73hrVi/Wffvv851OSsH9jIKnb1+XN15n9yAmx6EYtwr7DIEz3r2MymgpFv/0san2UsM9xKBO6LwQbid6LQydJ0gUgGDgL7M1xLJPrQ5YkaQvKpMqX+fjJt87NWCgy1NHR0emcaza9cmSSAR8nc7plX2cHqgS4KVTZbo4EezjxID6FSv4Z7JWVGhFUoT4/tkvh7l+38CyS3RLx8PciITL/kGFjajoX952hWqvaXDtmmbpaJD1BcsluRUvO7ojk7FaipkpTVP4lEelpyA+ugkqFiI9E5eGL5OyOIcKcKVb/OA5dDqpthwBP9Bk2hugE7H3dld6CrzupMeaMpuVa1ePs7m+hXGkAomUtfiVL4tC3L5LGDuwcCChfhUrGyIzy0mWXl59SXgH1WvHR4EY4uOlI3Ps3bkWy8+L6DNrnTvMGE3s3gpNrduU5lq5PQ3LK7t2o3L0RT3OUu70OVUAQjqPmKWXo6oFu6HT0Kz9GxMdiunUZkfwUu8btkTx9+ejzDzix/3ShqLLVGjUeXu4s27SYUd3H8+D2Q8a9NVlZx6CyQ9K+fGy+n7cHkTHZ1xUZ+wQfT/OhN18vD5ZMVUZfU/QG9p04h4tT3rRFQiySe3YPSHLzyltm/kHohivzH5KLOw4DpmJYNxc57DZpv6/FrsHraOq2QuUdQMTeUHyKZFNcewf4EJvr2a9YswJlqpTh2xPrUWtUuHu5s+jnhXz50XL8i/mzYvdX2GntwN4BxzGfoF82Jf98Df04R74+wLBuHvKj26T9oVRkdvXbom3Xjz7v+3Et9OoLU+v/dewiIV2bsXbmN5mHNwEvvDjl1WCfezn8o3MMQHFAS8YcgyRJVYAywF5Jku6hVBL5DiehcKdfs3RACLFSCFErMDCwsgkVjxJSFKrsGxGElDTvhDQr7UvoQ+UheqJP4/6TFIq66YhMNGAwmjBeOUbUd3Pp3qkrF/b8Sb0uTQEoWb0M+sQUEnLRGNs7OmTNO6jUKio3q0HE7Uf5XoQceR/J3RfJ1QtUajRla2O6k12JGP86TOruNchhNzDevoCmUkMkd1+wd0SkGrKGhjKRGhWPMVmPRw3l4x7UozERu5UuecSecwT1aJxnP4DGRUfD7u24Hx7BowQ96SaZHfsP0jD+AoYNM0jdvRb50d800T4hNCxHecUnU9Q1e7gu/NReZo8cgGHjfK7uOUO1Lkp6gdVLk5qoJ8kC7XPLCd1xcHFkx+wNFsso+clTJDcPJE8/UGvQ1GiC8VIOKnBDCslT3yZ51jskz3oH070b6Fd+jPzwFsZrZ1EVCQY7e9KP70SOeMD8yZ++NFW2u1f2B1vt6I5sSLSY98KgUpkS3H8cSVhENOnpRnYd+ZOQOtXMbJ4kKHMkAKs27eDNlo0s+pIf3kTlHYDk4auUWbVGmK7mGGYzpJA8sz8p84aRMm8Y8oO/syoF7LRKeZ3YSdof65HDbrPn57206qpM6ZWvXp7kxOQ8H98/Nmynd6236degP+O7TOTR3UdM6jGZe9fv0aN6L/o16M/bdfuALKNfPx+hT0JTtRGma7nyNXsAKQuGk7JgeEa+lEohM18Ackw4cthtxrZ4F2tR62egOZB/eNpz8L8w+fyPhqsKIRIkSRoNbJMk6SuUSmCmEGJepo0kSXclSSqe+9yMSmQ68MwlrDdu3DDunvIWI7ecQRaCTpUCKeXtwvITN6no50ZIKV8aFPfm5P0Yuqw/ilqSGNukHO46Lafux7D4yHWUjokg0OTDzQNXqB1SjzmHl5GmT2PdpOzOzEc7FjG73SS0jva8t2oKmgwK7+snLnP4+z0AVG9Th94zB6HyccW+03vI0Q9J3bqMtEMbse88WglXvXoCEReOXb0OyJH3Md39C/n+VURQRbSNuirhqkJG27gbaXvXZ6XfbN9cDracCsDFKWuo8flwJVz1wEUi9ytzBn8v+406K0dT/K1m6B/F8OeQz7POL9KuNnHHrzGlaTlGbjuHLAs6VSpCKS9nlp+6xWvlNbSqDg2Ke3HyQSxdNpxArZIY26gs7hka14N+CeVuXDL6dBNtVh+h3JNilG1WjfGHl5CmT2VLDtrnd3fM5ct2U3H19yRk1JtE3XrEyO1zADi1fg9nNx6iaJWSvPX1OHRuTkgqGacPVyDiY0g/tRc54gHadm9jenAT0+VnRBbqk0k7uBXHiYtBgOnqGU7uVyoVa1Blazz8kFNTEKmWK4bCUHhr1GqmDn+bETOWYJJlOrdsROniRfnyu61ULBNMs7rVCL18g6XrNyNJEjUqlWXaiLezzu8/ZT73wsJJMaTy+mXB577LqDZkRka46n7kyIdoW/fGFHbLvJLIBcnZDd3gGSAE8tNYDD9+zp8HHlCneW3WHVujhKtOWJxl/9WuLxnRNncMiWXIJhmRkoiuzyQA0kMz8tWqF6aw2+aVhKV8vfORkq+EWAwbFTpva1HrAxcBA4q08AvhVR4iKij+EdptSZKShBDOOX7/DvyMMpn8uhDieo5ji4FI4DSwDbgDOKII+CwUQpiL+lpAyooxVrnIMfOtR1fw+biX4rgyg7UpMVpPL5gQe0FgTUqMKR2td51tN6dYzde/hxLDgkTuC2LLW68oJcb9bS/djv86sE+BvzfDwr57JfsN/0iPIWelkPG7Q8a/ecYRhBDjc/x0y33cBhtssOFVwqscbVRQ/CtWPttggw02/LfwvzCUZKsYbLDBBhusiP+FqKR/R8WQYp3xZGHFWy4FBVvNV6p0yWq+ACSXgq3SLQjiKMB6hAJClWOh4stCL+eNjHpRWHNeQOVZxGq+ENZtu0pWXKkruTo/36iAiDFZT3LUGniVo40Kin9HxWCDDTbY8F+CbSjJBhtssMEGM1gvRuqfg61isMEGG2ywImxDSf+fQBVcCW1IL1CpMF46ijHUnHJBXbEB2ibdEEnKuHP6hQOYLivcOHaNu6IuUQUkid4e5/lx1hp6zxhE5WbVSdOnsWbiFxb1GMaun4abrweqLD2GVRl6DPXpOLYHDmUCOfDlRyz4cReyELxZuyyDQswZVRf9fprQOxEAGNKNxCUZODbzba4/jmXu1pMkGdIZMXYCLU/2Q51i5M+xX/Pk0r08efGoEkydz4ajdrAjfP9Fzk9XtBlem9yNom1qImRBauxTTo9ZgSEynuO3I1h44BrCTke3Tm8wuOebpO35xszn7qthfH1UWXRe1s+N+Z3rEHovmkV7s1ds34tNpLwqiJHTx1KpWXXS9al8O3E5D3OVl52DliHLx+Odocdwaf9Zti34AQDPot70WTgCF09XHNxB0iqrXo1n9pN+ZKuZH031ELSv90XOoFcwntqJ8cwBAOz7T0NdrAym+9dJ3TA/65xJH4+hUYv6GPQGZoydy/VLf5MbKzcvw9vXi1SDQgo3stc4nsTG07VfJ3oM6IJdkB9Hjx1j7rz5mEyml9JQWP75gjzp50RhtR3U5apj32mIssDt9F7SD262bFelAbp+U0j5bAJy2C1QqbHv8R6qoiWRVGrSzx6EjT8yYtZw6jSvjUGfyqfjP+XW5dv5pj1zzQwCgvwZ1tKcArvbsK44TRuMHKewHBsvHCb95B9mNpoqjdA274WcpKxeNp7Zh/HC4WwDrQO64fMx3TgLXy1k1OyR1G1eB4M+lQXjFnHzGToR/1kzmyJB/gxqqaxh+2j5NIqVyqJwvwfEo9BvvxBsQ0kvAUmSvID9GT/9UXpgmdSNdYD2wBagQuaCN0mSagHrgBpCiLQMJta9QDUhRH6rn9Ta5m+RunkJIvEJDm9Pw3T7IiLOfMLK+Hco6QfMaYJVAaVQFSmNYcNMAIKbTqDt8M74lghgasgoSlYvQ585Q5nbOS8R44p3F2dRb4/4aiK12tcn9PfjPL7xgOXDFzHjh3HM/XEPKwa2xs/Nkbe/+J2mFYIo5ZdNszCpQ92s/388fpXrGSylOjsNH/doTIlK1ZGDqtOoWWtml+1MvfkD2dd+Rp681Jw/iDOTVhF79hZNvp+Mf/OqRBy4yPXl27m8UBG7KfNOGyqN70LolNXM2/0Xa1avwvPyDt76YiMN1eGUcrXL8nc/Lok1J26wrl9TXHVa4pIV1tHawT78PEShTEjQp9Fh+W6a1GmCbwl/ZoaMJrh6GXrNGcyiztPy5HHfN7/z98krqO3UjPn+IyqGVOPqoQt0mdqX01uO8OevR1h24Svkh7dI3bgEhxHzMF47g4gOM7+Pl05kiLeYI/3oNoxaezS1W2Xta9i8HkEli9GpQS8q16jEB/Mn0r+95QWv096bxbWLN8z27dqyl83fbuPYgbnM/s9c1ny9HC9jDL3Hf0xI3WqUCsqeSM7UUOjUoiGnL15j6frNzJ2gaHkM6NIGQ2oav+w8zPPQuV0r3urakakff/JcW0WPYRj6lTMQCbHoxnyC8eqfiMiH5nb2OrSN3jDTY9BUbQhqO/SfjgE7LY6TvqBV9+gMPYZ3KF+9PKPmvseYjuMsJt2wbQMM+egxVG9cHWEyYfj1C0RUGA6DZmG8eQ4RYz6Jb7x2mrTdlilStE27Imfkt27zOhQtUZQ+jQZQoUYFxs0bzcgOoy2e1/j1RhhSzPM1e+ScrP8Phu3dDCTwEvhvRSVJkuQJbEThnLsH9BBCPMllUw34CnBF+cbOEUJsfJ7vf4xdVQgRm6HJUA1YASzJ/C2ESEOhxzhGDpk6IcQZ4AgwMWPXl8C0Z1QKAHVEfDQiIUPr4Hoo6lIFbQwIhThOrQG1HWqNhuKvleDklkNAph6DY4H0GDKZHsMz9BguXbtBMV8PAr1csNOoaVO1JIeuPsg3Jzsv3qFttRIAFPdxo7i3G+qAMqjDr+IkNNy/cA07V0cccmkzOPi6Y+eiI/as0oK6t+kogW1rAmBMyn5BNI72IARh6mSCihahiOkJmtQk2lQM5NAlcyWsLefv0rNmSVwzaDA8nfKKxO+99oiGpfyp1roOp7ccUdLO0K9wtaDH8PdJhWbblG7i4ZW7eGTQOfuXCeTG8UsEVyuNHPkAdanXwGTE9NdxNBXMtSSeBfnOZUSq+QchpG1j/tik9B4vnbuCi6sz3r4FX5GenKREu12+eYegwACKBRZ5aQ2F56Ew2g6qoDLIsRE59BiO5q/HcHALGLN1DxACyd4eVCqFm8hkpEr9KuzLo8eQl0LdwdGBLkO68MPSn/IcGzZjGAe2HADZhEiIBdmE6eopNGVrFOiaAFT+wUhObpjuKtF4DVvXZ88v+wC4du7aM3Uiug/pyobPv3+W+x4o7M4vDBlR4O0l8T6wXwhRBqWR/b4FmxSgnxCiEtAW+Cy3MJolvAp6DHkgSZIz0BB4h7z6pVOBwZIkTQbshBDPu4lFRWI2LYPCZJq3XDSla+DQdwbaN4ZnaSHI4XcwPbyObugn6IYt4sqRC2h1Drn0GOJwt8BJDzD22w9ZfHY1hmQ9Z3LpMURGx+Dv4Zr128/NkainyRb9PH6SxOMnSdQplUvVTefCrXsPMSHwkO3R59BdyIQuwIOUHHoIKeFx6HLoR1R+vzsdziyleJcGXF70C4lSGgH+fkhaHdrWQyjauAPRKvPQwvtxSdyPS6L/+kP0XXuQ47cj8uR599UwXq8UiLufJ09y8OQ/S78CQOfqSOUWNbl+XHnpH127T/XX6+Lu5wmSCsnBEXTOiKdxebQFANSV6qIb9Qn2vSdYPJ4Tvv7eRJrpMUThE5BXjwFg5pKp/Lh3LYPH9Tfb32NAF2JVnhQpVgJjlFKBvoyGgjUhuXmZ6zHEF1yPwfjXCURqKk4frcPpw1WkHdqKm4cr0TnuZUx4DF4W9Cv6T+rH5m+2kJpLv6Jeq7rERMSQakgDOXuKVjyNM2MXzoS6fG10g/+DfZf3kFwynxkJbcvepO3PrnS8c+lqxITH4G0hX4MmDeDnlb9gyKUTkYkqdSuDQr/zwgR68F+l3e4EZJKlrQc65zYQQvwthLiZ8f9jFCohn9x2ufFKVgwoF7hLCPE3ECdJUlZzQggRDywA5qHosj4PFkj3zX+a7lxEv/oDDBtmIT+4hratIj8pufug8gxA/81k9CsnU77Bazh7WIi/zodv6rN+/2FCnSFotHZUyKXHYImjKr848d0X79DytWDUKvPblWaU+ebABd40BKPKPDe3joOly89hc2n+Jn6vNZr7W05QemDrjKKRUHkVJe3AOoxXjqD2DkRyyX7RTLLgQVwSq/o0Yf6bdZi1/RxPDdmtzehEPbeiE6hf0q9AmgeZUKlVDFo6hoPrdhKbocewZc4GytStyJtT+6By8UBOiIUMZtHc12q8fgb9opHol03EdPsv7Ls+R8OpgFoR096dRc/m/Xmn80iq161K++5ts479vG4LxqjbyIYk1J7ZUqMvrKHwf43cegyd3rGox6AKKgNCJnn2QFLmDkXbtDP2jnl7NbnvZaYewwkLegy9R/Xi2083WCz23OVuvHkB/Rfj0a/6ENO9K9h3VIb4NLVaYLp1kZyNvYJoMZSqWIqiwUU4tuu4hcQVNO/UDF6ytwDKeE1BN0mShkqSdCbHVhjyPj8hRDhAxt9nadcgSVIdFDbr/CeGMvCqVgy9gcwmwU/kpd5+HaVmr5ifg8wCb9my5ezHpmz9BcnZI2uSOQuGZDAZATBeOoLKLwgAdenqmMLvoKlYH4eeU/AO9EVSqXLpMXgS/1w9hlCqtapttt/f14eIJ9kjYJEJKfi4WiYW23XxbtYwkrpEDeybDcQuZABHL1zj7Zb1KGZSKitdgCf6CPNrSwmPwzGHHoJjgCcGC3oI9389QbH2tXEVWsKjojA9/huM6UTGJeDjoEby9M+y9XPREVK2iKLH4O5EsJcLD+KyW78PfV5jy69bce40hvjIJ3jk4MlX9Css6zG8NW8YUXcjOLgmW/c8IeoJK4d/ytoxS5EzVe5SUxR1sqe5yl2flH0fQ/ejKloyTxqSuw8O7y3ix71riY6Mwc9Mj8GX6Ii8anSZ+1KS9ezaspfXqlUwO+7n7UFE+GNUzspz8SwNhZ8/n8novl0ALGooWBN59BjcLekeFEc34j84Tl2JKqgcDgOnoQosjaZ6U0zXz2FXrw0OQ2YiObkiZBmfHPfSO8CbuFz6FYoeQ2nWn1jHp1s+pWiJoiz8eQEBwQH4F/Pnq93LGTFrhDJ5/M7HSE5uyr1MyvVM5LyX5w+h8g8GQF20NJpardCN+xJt+3fQ1GiBt7+3ma6Gd4C3BV2NCpStXJYfT25g2a9LCCwZyJJN2fM0KrWKxq83AmXM/qVQGNrtTHmAHNvKnL4kSdonSdJlC1unwuRJkqQAFC66gUI8f+XjK1cxZExKNwdWZWgyTAJ6ShnNAkmS3kAh02sDLJIkyeLblVng+/btqxwYXALJ1VvROihfG9Odi+bGOQRg1KWqIccpQyPiaRzqwLIY/zqC4Yc5PL4ZxpXD56nfJQQonB5DeC49htfKl+NB1BMexSWSbjSx++IdmlbMK25/LzqBp/o0qgYpD77p7jmS9q5i4Nu9kCNuUr2hwkHvVaM06Yl6DLm0GQxR8RiT9HhlaDMEd2/Mo13KkIZzCb8su6Kta/D0VjhFTU7cD3vEY5MD6TLsvhZG87btEAnZko7NygUQel/5/SQllfuxSQS6Z+sdL/lqFbe+nUfqH8v4a8+f1O3SREk7o7yeWtBj6DChJzoXR36Zvc5sv5OHC5Ikcf/ibdRFS2G8chrUGtRVGmK8bj78kXOIUF2hFnKU+cQ0gIiPxvDFJHq3GsihnUd5I6P1X7lGJZISk4iJMv+gqNVq3D0zBJs0ahq3asCtG8qQUbESioB9pTIleBARw8O7t15aQ8GayNJj8MzUY2iM6UoOenJDCskz+pIydygpc4ciP7iBYe0c5LBbiPho1GWqkH5iB/ov30ckxXN85wla5tBjSElMJi6X5sEfG7bzVq0+9G8wgAldJvDo7iMm95jCvev36Fm9N/0bDKBP3b4gyxg2fYbQJ6GuWA/j3+ZzMpJzjneybA3kWGViOnXbCvRfjEO/5F3Stq/GeG4/qxesoXW3lgBUqFHBok7Ebxv+oHutXvSu35dRb44j7E4Y47pPzDpes3ENHt5+CJD3oSlsuVtxjkEI0VII8ZqFbRsQmfHBz/zwW6QZkCTJFdgOfCiEyF9jOAdexXDVbsC3QohhmTskSToMNJIk6QzwKYrC21VJkrYB0zK2/GBMO/gD9l3HgiRhvHwcEfsYuwYdkSPuY7pzEbvqzVGXrAbChDAkk7ZL6Vqbbp5FFVQeh34zAcHDX8+ybcnPvDV7MHMPf0GaPpW1k5ZnJZSpx2DvaM97q97HTmuHpFZx/cSlXHoM76D1deOjmbMZOX8BppSndKpVhtJ+Hizfc46Kgd6EVFR6LTsv3KFt1RJm3eU9l+5x7m4E8d9txuRVgkan52OfLHN2XHZIaeu9c9nTStFmOPP+Wup+Ngy1g5bwAxcJP6BUjFWm9cK1VABCFiSHxXB2yhrUSLzfqjJDxr2PrLajS+fulJBjWbbtIBUD3AkpW4QGJf04eSeKLl/vRSVJjGvxGu6OSq/sUXwyEU/11CyutCwvHzxPpWY1mHV4KWn6NDbkKK8PdixkXrvJuPt78vqorkTcCuP97Uq45uH1uzix8QBl61Wk0+S3EEJgCruJpmx1NOVqYDx3EBEVhl2LnsiPbmO6fgZN/XZoytdCyCbQJ5G6OVsrw2HIbFQ+RZWW6uQV1L8zh2P7T9KoRX22ndyIQW9g5ri5WfY/7l1L71YDsdPa8eWPi9Fo1KjUak4fPcOv3ylM7z0HdaVu41roivvw4QdTGDx0GCaT6aU0FFp07sPsD8bRsG5Niw9zYbQdkGVSf12JbshMkFTZugdt3sL08Bamq/lrWKQf34FDz9HoJi5DkiTSQ/fz+7d/EFQ2iLXH1pCqN/DphCVZ9st3fcHIts+TX8/IlklG6JNwyBjqM148goh5hF2TLsjhdzHdPI+mVms0ZasjZFm5l79/k6+/Uwf+pG7zunx3bD2phlQWjM/uCXyzewVD2gx/bp6ad2zG/q0HqVqvynNtn4f/IlfSb0B/YH7G3225DSRJ0gK/onxTNxXU8T+ix5AnE5I0E0gSQnwiSdIhYL4QYleO46OBCsATQC2EmJKx3wW4ALTNnGCxhJTFQ6xykaOXWh4CeREsW1IIZyCKAAAgAElEQVTwiJrn4beR1uVK6rggyGq+Jnz03OHMAmPR29Z7VhuvsR6/zsnD859vVEBYkyspdb7lUNIXRdeNac83KiC2DH/u/GeB8cZX1ruXB8P2vvTytA+C3yrwgzrv3g8vnF7G6MrPQBDwAOguhIjLCOsfLoQYLElSH2AtcCXHqQOEEBfyeszGK9FjEELMzPF/iIXjS/M5LxEo9X+WMRtssMGGQsIKYagFghAiFmhhYf8ZMpQthRDfAd8V1vcrUTHYYIMNNvyvwMaVZIMNNthggxn+Wz2G/0v8KyqGpO15+W9eBAniuQsGC4y0LXut5ivCLuD5RoXA44XnrOYrUTg936iASDhovTmelvZ5I8BeFFbVVraihoL9+0ueb1QINNo03Wq+0i8/fL5RAWF4xb7Dr1h2Xgj/iorBBhtssOG/BRuJng022GCDDWawptLjP4V/XcWgrV0H53dHgUqFYcd2Un76wey4wxsdcez0JkI2IfR6Epd8gun+fTObgTOHUKNZTVL1qXw58XPuXjYnmQOYtn4G7r4eqDVqrv15ldXTv0aWZYIrlmDInBE4e6kVhsn1n2O6cwNN5do49H1XoUc+tIPUP/ISkAFoajfBafQMkj4agemu+RBZ01l9CW5WDaM+lT0TVhJ9+V6e8+tP6k6Fro2wd3PiqwqDs/ZX7tOcKv1aIUwyrvYClYMDyDJPN+8kfvXPZj7c+nXBtWtbhMmEKS6B6OmLMYYra2sCVszBvkp5DOevEPHuRwD0nfkOVZvVIFWfysqJX3DfQnlNWj8dd18PVBoVN/68xvrp3yBkmTfH9iSkd0sSY5/i62aPpLVDpKWR8vt2kjaYsxc49eqOY4d2YDIhxycQP3chpohItDWq4Tb63ewyLB5EpVHLuLLnDB1n9Kd8s2qk69P4eeJXPLpiXmZ2Dlr6LB+LV3FfZJPg2v6z7Fxgfm/Uleuj6zcZ+UkUmEyk/7mP9INbLN6/TNuUzycih90GtQb7rsNRBZYGIZO2bRVo7KxClS10Tsj6/CVMC0vhDdBmZj9KN6tKuj6N3yZ+TYSFZ6zZpO5U7tIYnZsTCyq+k7XftYgXnRYPx8HVERcfLZLaDpGeRtrB7aT+Zn4vtS07YN+qM8gywqAnZdWnyI/ug1qN49BJqIPLgFpN2tE9cOQHxs0eRYPmdTHoDXw8bsH/Y++s46M4Hv/9zPlFIUISggR3dy1etHgFKO5SHAqUFoproYq1BQoU2tLSFimuxbXF3WJECLG7y8n+/tgjyeUuIUDaH/1+8s7rXrndnZ2dnZ3b2R153ly/6Dx6/YsfP8E3wEdmNQGj3hnP45g4KteqyKjpwyhWphjI86h+ylZmZCLL/4GK4Zkzn4UQViHEefs07B+FEMH25fNCiAghRGi6ZU2G8L9nJPkJIUYLIYxCCG/78uvp9k8UQlyzf18rhGgkhNiabt8OQoi/hBBXhRB/CyGcoFFZn60Cz/dGETdpArF9e6Ft0hRl4cIOQUz79hA7oA+PB/UnedP3eAwe5rC9SuNqBBUJYsRrg1k+6QsGzHRkzT/V4mHzGd9qFGOaj8DL14vabeoB0GNSL35cupHEDwZh+nk1urcHglCg6/UeSQsmkTixL+o6TVDkL+wcqU6PtkVHLDcvO20KaVyJPCGBrGk4lr3vf02TWb1dpuvOnrNsfMMZzX1tyzHWt5jE920+QOnthSX8EfffGIBH68aoizrOazBducXDt0bwsNMQknYfwXdsWgUT9+2PPJo0P3W5UuOqBBQJYtxrw/hm0jL6zHSNgvls2EKmtBrDpOaj8PL1olabOqnbdn69laltx4OQiB46kkfdeqNv1hRViGMema/fILrvYKJ69sew/yBeQ+U5kilnzxPVewBRvQcQPWIMksnI9UN/UbpRZfyKBDK/0Wg2T15Jx1n9cKVDK7eysOk4lrZ5n5BqpSjVqFLqNq27Dk39NkjmFExbVpG88D1Ulesj8hVwjkgrh02Pt1bXkjHghsWjMK6YjqZdH7SdBmNYNZ3kBcNRVWmACHDRH/IMVHbykjEodJ6gyPzZr0Pr5ixbPDPT7RlVvHElfIoE8sVrY9k26Wtaz+zjMtz1Pef4pv2HTusbjOjA5a3HWdX2A4Q9XQnjeqOp2xRFsOO1TPlzLwkT+5EwaQDGrRvRvytj0dS1GoFKLW+bPAht03a0fvN1ChYJpmv9HsyduIgJczKfvzFt+Cx6tRhArxYDeGwHHUaERjJj9Dx2b9mb6X7PI+k5Pq+qsoPEMNhR2OWBFOCtZ+Cy04ePBYZliO8d4BTQEUCSpJ3p4jsNdLcv90y/kxCiErAQaC9JUmngDWChECLbUxVVpctgCQ3FFh4OFgum/fvQ1nVEE0jJyWnH1Dmbz9doXpODm/cDcOPcddy93MnjAj1syAS7LUng5iFTPITeHdvjGJTFSmOLDEWKCgerBfPx/air1XWKU9e5D6Ztm8DsPNGoaItqXNksmwtFnLuF1ssdt3zOneUR526R/Mj5KTLFnt6AysWwxsYhGU1gsZC44wDuTeo4hDWeuiBvB4wXrqAMSOPnGE6cx5aOd1+1eU2ObD4AwK1z13HzcsfbRX5lxJRnnHdZrHJxLA/DsIbJ186wZx+6BvUcz+HseSSTnK6US5dR5nOeRKVv8hrGYycxG1Mo26IaZ38+DMD9czfRe7rh6QIJfuuYXBFbzVZCL93BOx1Nt8XYN7FcOgVmk8whslqwnD+SOd76wBawmFPXiYCCWG/KExSlpCdIkoSU+CRnUNlIWXZmPw/CG6Bk82r8tVnOr9BzN9F5ueHhooyFnrtJoosyJkkSWg89+SsXwxYXjS1GPseUY/tQV3e8lhjS/Q61unRQPEleVigQGi2SxUzVOpXZ8ZNMFrh09goe3u74usBuZ6aIh5HcunI7FVnysvoXsdv/mJ6XlXQYKP4c4Y8BwU8X7MY6HsAHOIPxnqVxwGxJku4A2P/PQWYpZUtKPz9sUWk4EVtUFAo/Zzyvvn0HfL/bgMfAwSR+vtRhm0+gLzHp0MMxEdH4BLjGO09ZO41VZ9diTDJwfLtMm1z98SrendwbzyXfo3tnMMYfViHy+iHFprGIbLFRiLyO6VIULo7C1x/LedeoE4/AvCSGp3F+EiNi8Qh0vgFnpYo9m9F25SjUBYOIniOjKyyR0ajyuUZRA3h1akny4VOZbs8b6ENsuvyKjYjBJ8D1j3b82ql8cfZbDEkGTm4/lrq+Wc9WDP1sDKqgQISnDAy0RkWh9M88Xe5tW2M8fsJpvb5ZYwy75SdD7wAf4tIh1OMiYvHOAgmu83KjTNOq3PzzIgD5y4WQJ8gH2+NHSOlu9tKT7OOtbWF3UJWtKd/o8uZDma8AkikNV/0yqGxr8pMcHeXkGehDfLr8io+IxTMg+2Xs0JKfqdCxPm9/Mw5l4eIYVn8GgC0mCkVe52upad4BzyXr0HcbhGGNHNZ84iCSyYjXV5vx+mwjpq0/kMfH2wGfHhUejb8L7DbAB4snsmbXSvqMejfb6X5e/YvY7X9M2a4YhBAqZKpptvgLQggl8qy839KtfgcZa3sYKCWEyBITm0HlgDMZ1p22r8+msodZNvy6hZh3u5G4cjluPRxeXLKF+H2qWT2nMbBGb1QaNeXrVgCgRY9WrJ7xNQmj3sG4/kvc+o9zmayMeGR99yEYNmTVDpz9dGWmv9bu4cCHazFdvE7eQd2eGY9H2yZoy5Ug7tvMm2SfB7u9oOcMRtToh1qjppw9v/au+4OxDYeycfZabEYT3iOGPjMe/evNUJcuReJ6R1CmwtcHVdGimE6cepq4bKdNoVTQ7dMR/Ll6J7EPHiGEoN3Ud9k6a10m+O4MeOs3+rrEW1tO7cX2JBr9yIVo2/fDFhWGU6F8QVS2Uu+dZVPS88r1aWa/jJV7ow4XfjrE9snfYP7rFG5DJ6WL1DmelN1bSBjVA8OGFeg6yjdyZbEyct/X0C7Ej+yGtk1XdC5Mjlwla9qIWfRo1o8hHd+jUs0KtOrSIttpfx5Jz/H3qio7FYNeCHEe+SZ8H3D2TXQdPgbwQbbefKq3gY127OvPQNfnSKvAufS4WidvSMc5Xxsqs1Ss0VEo/NPqIoW/P7YYZ8zyU5n270Vbtz769h3Iu3wVC7Z/QmxkLL7p0MO+gX5OJMf0MpvMnN59khotZJvORp0bc2KH/DRsPnkQZbHSSLHRCJ+0Zg+Fjz9SXDrKp84NRYEieExejOfi9SiLlcVt9Ax0bw3AY+Zyuu2YRdKjx3gEpT1ZegT6kBiZecdjZkoMj0UyW3BrIjdlqQL8sETFOIXT165C3oHvEDHiIzCbHba5N6mLrlp5Cvz0JY8jY/FJl18+gb48fpT5fASzyczZ3aeo2kLGlMdHP0Gy2YgNj0ZKSkJdtjQASn9/bNHO6dJUr4pHrx7ETpzilC5908ZYHjzA/+tljNo+h/jIx+RJh1DPE+hDfCZI8M5zBhB9J4Ij3+wAQOuhI7BkQQZt/BBt+34Ijzzoek9GUaCYbJDjhLcuhH7wTNwmLUdRqGRqWGw2Un7/FsMnYzCungNKpb0ZSNaLoLKxWeXmKIsJoUqL60Wk0HmhyhOMKk8wCZFxeKXLL69AH5dNRpmpyluNuLz1OPERsQiVBtQahKc3Cl9/bI+dr+VTmdM1NWnqNcV84SSaJu3wmLQA4ZUHSZIc8On+QX5ER2aNT9+1ZS9lK5fOdtqfR/8rbwyGdH0II+z9CM8MDxRGNoUYBmDvCygB7LbjtN/m+ZqTLgEZyXNVAeeeWBw55z2D5QlglqtXUQUXQBEYCCoV2sZNMB11NO5QBqe2fKGpXQdr6EMMv27h8aD+jG89mlO7jvNaZxl1XaJKSZITkojLcKPTuelS+x0USgVVG1cn9JZM8419FEvZ2rJpj7JsFWwRoVhvX0UZGIzwDwSlCnXtxpjPpjM6MSSRMLQTCWO6kzCmO9Zbl0n+ZCrGTStJ/GAQG1pN4dbOM5TpLPeXBFYphikh2WVfQmbKEyIjuCMv3EZTqgiW8EhQqfBo1Yik/Y7NV5rSxfD/6D0ihn+ENdbZHjdp31GMZy7ysMtQzuw6Sf3OjQAoVqUkyQnJPMmQX1o3XWq/g0KpoFLjaoTZMeVP19++cBN10RC5j0GlQt+sCcYjjmYwqpLFyTNxDLETpmB77Hzu+mZNSFjxDVG9B7Ck9SQu7TpN1U4NAChUpTiGhGQSXCDBXx/7JjpPPb9/vDZ1nTHBwPSqA5lb/z2SZw0AqwXTz8uwhd9DVbk+1svpmteMySRN60XynEEkzxmE7f51jKtny6OS1JrUikBZohIYklB45X0pVLZ8kbQIlRbJ6lg5Pq9sxngscaFY4kK5tus0FTvL+RVcpTjGBMNzVQxPwmIIqVeesAu3URYojNDpkJIS0dRpgvmM47VUBKb9DlVVamONkMuDLToSVbkq8tvEtBFIcbEc2HE49em/XNUyJMUnEZPhYU2pVOBtd0xUqpTUa1aH29fuPH+GZENWpGx/XlX9Y8NVJUl6Yqei/iqE+Aq5EpgmSdKcp2GEEHeEEIUlSbqXaURpWgj8KITYJ0nSXSFECLLNZ5dsJ8pmJeGzJeSZtxChUGDYsR3rvbu49+6L+dpVUo4dRd+hE5qq1ZAsFqTEROLnzXGI4uy+M1RpXJ3PDi0jxWDii3GfpW5bsP0TxrcejdZNy8RVU1Br1CiUCi4e/Ytd62RY7PKJX9BnWn88vPsimVNI/mYx2GwY1n6G+/h58hDFQzuwhd5D26k31jvXsJw7xrN0d995QhpXotfhRVgMKewel+b30W3HLDa0ksnk9Sa/Tan2dVHrNfQ98SmXNh7gxCc/U7F3CwrVL4fNbMUaE4fCw51Cv68k/pddmG/dI++wnpguXSf5wHF8xw5AuOkJWPwBAJbwR0SMmAZA/jWL0BQpgHDTU3jPOmzjvyLqfiQLD31JisHEynGfp6Zr5vZFfNB6LFo3LWNWTUKlUaFQKrh89CL71u0E4O1J71K4bBEkScLyIBRVkRDyfb+a5K07sNy5i2f/PqRcvYbpyFG8hw1G6PX4zJTTYo2MJHainEZlYADKAH9SzqV5cVzdf47SjSsz8eASUgwmfhy/PHXbqO1zWNJ6Et6BPjQd0ZHIm6GM3CZjuY+u2cXJTfvTlSsbtugwtB0GgM2K+aQdb93iHawPbzpWEhkkPLzR9/8IJAlbfAzG7z9BEVAoR1DZNlMCWDN/jnsuhDdwc995ijeuzLBDi7HYh6s+1YDts1nZWsa8N530DuXtZWzk8c84t3E/h5b8zO6Z62k7tz+1+7VEslgQCDwXrSblwA5sD++i69IHy51rWM4cRduiI6oK1cBiwZaUQPJXMsHWtGsLboMn4rlAbkpLOfgHm1dvoUiJwvz45zpMBhMzx8xLTdeaXSvp1WIAao2GJRsWpOLTTx0+w6/rtwFQplIp5n49A09vD4DlwHSeq4naUbZXgFj9snomdlsIkShJkgs/S0dcdmbhhRC/I6NhPwZaSZJ0Nd22xUCkJEnz7MsHgHF2OiBCiEb25bb25U7IF00NmIGPJElyPWA8nR41fS1HrtSwmzmHxFjVMOf8flcfzFkkRluvqGcHyqamJeQcEmNecM4hMZaEBT47UDb1YVfjswNlV68wEmNutZxDYoyoG5ZjcbU6lGNRcSx0/0tjt3sU7pTt+826ez+/9PH+CT3zjSGzSsG+bdqzwkuS1M7+9TsXYcdkWG6UYfkAcCDd8s/IfRO5ylWucvVK6lUehppdvXLWnrnKVa5y9V/WvzUqSQjhI4TYLYS4Yf+f6dhhIYSXfTLy55mFSa/ciiFXucpVrnJQ/+KopPeBvZIklQD22pcz0wzgYHYj/p9gJQ296f3sQNnQDM3LjfBIryGHvHIsrn6mnEsXwPsJzuPCX1STbDlnWzI37HmmvWStKSE5ZwfZaWPO5ZdwOanlxZSTmGyA98/MyLG4elYb8+xA2dTWyjnX95QTsv57A1HbA43s39cgN7tPzBhICFENCAD+wHlkp0vlvjHkKle5ylUO6l98YwiQJCkcwP7f6clJCKEAFvEchAj4H3ljyFWucpWrf0vPMxtcCDEQSE+WXCFJ0op02/cArobQTcnmIYYC2yVJeuCS2pCJciuGXOUqV7nKQT3PqCR7JbAii+3NMtsmhIgUQgRJkhQuhAgCHrkIVgdoIIQYisyp09inFGTVH/G/UzH0nTaAKo2rk2Iw8fm4JZl4KEwjb6qHwiVW2T0UCpcJYeDsoRR212EzGFHl8QQhiPthJzErfnSIQ1+jPIFTBqItVYTQ0XNJ+CNtZnW+CX3xaFQDFIKeh/5i7bSv6TmtH5UbVyPFYGLZuM+46yJdE+1eBUqVkqsnr/Dt1BVINhsVX6vCkMXv4enlgTkukYgfDnFzxvrU/YRGRbnPh+FZsSjmxwlcHLgU44O0OQraYF9qH17MnQU/cv8rmW5ecEArFr3bmLz5fJAkG48jH7+w54RGqyZQr0NoVEgWKzHf7ybyS0dvAY9aZSnwUX/0ZUK4M2whcXbYoCbYn6Ir3gelAqFSEbV6G3x/gM4f9aZs4yqkGEysH/cVDy85zl5V6zT0/XI0foUDsFltXNx7ht/nyaz/jlN7UqKOPG/J11OJws8PW1QUKJUYtm0jeYOjN4db167o27RBslqxxcURP38+tshIOd0DB6KtI1NnX1vwPQd/P8TQ6UOo0aQGJoOJhWMWcfPiTac8e6rp30wjqFAgA5sNdljfZVBnBnzQn+3rd1C5XiWMBhOLxizi5sVbmcY17ZuPCCoUyKBmjgj42gNb03xKd85u2EdI3bIv7aGgyhOENSkWyWxw2h+e39+h17T+qWX/q3Gfuiz776/5MF3Zv8w39rL/3ufjCCoqz47Ok98bhbsHtuhHGHdtw/ij43XUtnoDXduOMirEYCDps4VYH9xDVbI07iPG2UMJDBtWPzPN2dG/iLr4DegFzLX//zVjAEmSuj/9LoToDVR/VqUA/8E+hnR+DxeEEGeFEM586gySPRTyM+K1QSyb9AUDM/VQmMe4ViMZ3Xw4Xr7e1LF7KAyZN4L1c9dw543haAoGknj4DLdaDcar7Wtoijuy8i1hjwibuJgnvx9wWK+vUgZ91bLcbjuM262HUqxSCdoN7khgkfyMeW0oqyZ9Rd+Zg1ym69NhC5nUagwTmo+0ezvURSgUDFownIg74Rws3ZeUqCdE7XKkbebv1gRzXBLHao/kwfLtFJ/azWF7yY97EbP3fOqye+mC5O/RlI0L13Pzwg3uXr7LT59uemHPiYltx6J012F+FMuVJsPJ274BuhKO+ZUSGs29MUuJ3eI4S8n86DHXOk7kasvRXHtjPAFDO1G9QwP8iwQyo9FINk1eyZuZ+CfsW7mVWU3HML/NRIpWK0WZRpUB+GXGWua3nsj81hNJ/uUXsNmImziRmF690DVp4uTNYb5xg5hBg4jt1w/TwYN4DpKvj6Z2bVQlSxLTvz8xQ4bQdXAXGrSuT3CR/PRp0JclE5fy3uzhLtMGUK9lPQxJzjdX/yA/qjSowuPoxwQVDqRPg34snfgpI7KMqy7GTOIqWr8CidFPyFso30t7KKxsPQVLwiOUHpkTbZ/H36Fy42oEFgli9GtDWDnpS/rNHOwy3NJhC3i/1WjGN38PT19vareRf+6fDl/IpNajmdx2LEKtwbj9V+KG9ELbsCnKghm8HQ7s4cmwPjwZ0R/D5u9xGyA7AVju3eHJyEE8GdGf+A/H4z58LOTAw7IVW7Y/L6m5QHMhxA2guX0ZIUR1IcSql4n4P1cxkMZuqgRMQkZvZ6kazWtxINVD4Rpu2fRQeNpWmL9oMJdPXEJfsSSmWw9wr1MZzBbitx3Cs6mjV4E59BGma3edZ7BKEkKrRqhVCI0apUpJSIWiHLan66bdqyC76SpeuQRCCDZ/shFbkonILUfJU6uMw37+LasT/oM8Qu3R78fJW7986ja/VtUx3Isk6VqaKbt7iWCenLlBlUZVObh5H5dPXCRfwYAX9pwoXrkE5tgnpNyPRDJbePzbYbxbOHoLpDx8hOHqPaf8kswWpBQLAEKjRigUlGlYkZM/yxXI3XM30Hu64+XCP+HGsUuA7J/w4NId8rhAaevbtMH68CFWuzeHcd8+tPUcPQHM58+D3d/BfPkyCn8ZdKgqXBjzhQtgtYLRyO3Ld2jTozW7N8s476vnruLu5YGPC08AnZuOzgM6seHT7522Df5oEF/P+hqtTsvB3w9liMs5/3VuOjoN6MSGT53d/gZ9NIi9c75HrdNwaavMunoZDwUAIRRIWYwyex5/h2rNa3LY7tPxvGU/vYpXLoHQqDFu+0X2WDm0D3XtDB4rhgweK0+jMJnAfj5Co3luGnFmkiQp25+XPE6MJElNJUkqYf8fa19/WpKk/i7Cr5YkKfOnjHT6L1YM6eUFPHOsmm+gLzFhaU0osREx+GbiofDB2ml8ffY7DOk8FB5cv0eN5rVQBfqi0KhR2Vnv5ohoVJnEk1GG81dJPv4XJY6uo8TRdfx16DxavY7YdHz72IgY8mbiVfD+2g9ZdnY1hiQDJ7YfI2+gD0q1ilI1y1J9x0yC3myIZ4UQh320QT6YQuX4JasNS0Iyah9PFG5aQoa3585CR1x24tUH5K1dGv+CATyJeULVxtXwy+/3wp4TE7/+AG3hIMLmypPezeExqAOzl18A6iA/yuxaSoWTXxPx1c/ovd0z+CfEZOmfoPdyo3zTaly3+yc8Vd5gPxT58mG5mdbUY4uKQunvbOyTGlebNqSclDlFllu30NSsCVotwtubSnUq4hvgS1S6MhYdHoWvi3PtPb4nm1duxmQwOayv3bw20REx3L5yB4VSSUxE2nlGh0fj68JfoNf4nmxe+TMmgyOSo3bzWkRHRBN55T4KpYKEiDSg3It6KIw8/hlKr0CsiZnTiJ9HPoE+Dr4mWfl0vL/2I5adXYPRXvbTq3z9SkgGA7awp5C9KJS+znmlbdOBPKs24NZnMEnL0zxWVKXK4P3lavJ88S1JXywGsLzsuf2v0FVfNentTUlXgVXIEzey1nNw5Gf2nMaAGr1Qa9SUryuTKr8Y/ykte7bGf3xfUKmQzJb0EWUr0epCQWiLF+RGg57cqP8u5epWwDOvi6erTOKb2/Njhtbom+pVIBAIIXD3dud0qw+I3PInvo0rudzXMXqJouO7cn/5NqzJjjen5Buh3P38N0pWKUnPKX25e/kuVosty3Rl5TmxcspXJJ27TqEFI555fq5kDo/mSouRXGowGN8ujVFrNa5OyOW+CqWCXp++x6HVfxDzwLFPrlq7ulguu4DyZhKXrnlzVKVKkbRRfjJPOX2alBMn8PniC7ynTuXK2SuuTyBDfEXLFiV/4fz8+YcjSVSr09JtxNusWbSWzJSxvD6N66iLuN4Z8TZrFzkRaDKNKys99VBYWnsE1vgIVJ45M5fEtU+H67Bze05naI0+DmXsqUpVL4M1wpG75Coa07YtxPXvRvK3y9G/leaxYrl2hSdDe/Nk9GD0XbsDvPSklP8VP4ZXTU+bkkoDLYG1wkUpW79+/YarV68mX716Nfnew/v45k97GvQJ9H2mh8KpdB4KYbdCmfHuR4SPXYBkNGG+L0+OUgf6YckinvTybFEXw/lr5OnYjJCNC/AvkA8hBD7p+PbZ8So4s/sU1VvUJDYiBslm49QfcjOBLcWKzWJF7ZtW2ZjCY9EGy/ELpQKVpxuWx4l4Vy1O8andqXvqMwoObE3IyI6UXzGKmnvnUbBfS45u/ZNfl20mMS6B8LthL+w5ERsRAxYr7pVLyPkV5Is5Mnv59VR+vVpTbM1UtIVlUKCjf4IvTzLxT3h7zkCi7kRw4JvtTtuqtquL6fDh1KYhkL05rNHOT8OaatVw79GDuMmTHfwdktatw7B1K4o8eajRpAaPwqLwT1fG/IL8iclwrhE/UeYAACAASURBVGWrlaFExRKsPbqGxT8vJLhIMAt+mE9QSBCFShTix/Ob2HrrNzRaNeM+GUte/7z2uPyIjYxxEVdx1hxdzaKfFxFcJJj5P8xLjeuH8xuZfGMNKq2a9osH4+4vT/J8UQ8FAMliko11xIvdNtJ7OzzO4Gsil/2sy9jZ3Seplq4pUqFUUKxicUhJI8gq/LL2WEk5tBdNnfpO660P7j11zivvtPE59b9o7flKSZKkY4Af4NQG0L17926lS5d2K126tNvV/ZdolOqhUIrkhORseChUS/VQ8PKVf1SGizfQlilK/M4joFbh1aYhCXtdW21mlDksCrca5Xm8cTt3Oo3i4Y0H/HXwHA3s6SpepSQGF+nSZkhX5cZVCbv1kFsXbiABNVrWQaiVBL3ZECnFgjkmIXXf6J2nCXrzNQDytavN4yNy2/uZ9tM4WmMER2uM4MGK7dxd+gsXBy7hZNOJnHtrFqd2Had5t9ep1bIOEXfCXthz4uaFG+hLFybl4SOEWkXeNxrwZHfm2Oj0Ugf6InQaotds58ZbH2B5HM+FnSep2akhACFVSmBMSCbehX9Cm7FvofN04+eP1zhty1c0CL23O4YdO1AWSPPm0DVpguloBn+H4sXxHDOGuMmTkeLSHUehQHh5YdiyhfjZs4mJiOH3Nb/TvHNTAEpXKU1SQpJTZbr1u228U707Pev2YkyncYTeCWX8mxO4e/UuHcp0ok2xdrQt9gZPYp5w+/JtHkc9pnSV0iQnJBGbIf+3freNbtV70Ktub8Z2GkvonVAmvDmRu1fv0rFMZ9oWe4PZJXqRFJNA5OX7JEU9eSkPBQCUakC8MAE2vbfD6V0naGD36Sieia+Jc9lP8+kAqFC/Eg+u3UPhnw9FgN1jpWETzCccPVYU+dO8HdQ16mALk8upIiAQFEr5u38AyuCCAHdf6OTS6d/qY/gn9Z8eriqEKA0okd3iMtXZfaep2rganx9ajslg4stxn6ZuW7B9CeNbj0LrpuP9VR+keij8ffQvdq2T3brqv9GQlj1b4ysg8eAp8nRtSd63WxP30y5Sbt7Hb2QPjH/fIHHfCXQVSlDgy6kovTzwaFwL//d6cLv1EBL+OIJ7nYoU3fYlSLD3wHl++mQjvWcM5JNDX2EymFieztth9vbFTG49Bq2blrGrJqWm69LRv9mzbic2q40V4z9n2NJRaLu/TkpsPJeGfkbRCV2Jv3Cb6J1nCNuwn7KfD6fO8aWY4xK5OGipU95kVMWvx1DU1wMvX28sZgu9pvZ9Yc8JhVKJNdGAwsuNsvs/J2bTXozXHxA0thvJf93kye6TuFUqTtGVk1B6e+DdrAZBY97hSrMR6EoUoMDUvkiShBCCyOVbOLLpEEElCvDhwaWkGFJYP/6r1HRN2D6P+a0nkifQh9dHdCLiZijjt8kM/8NrdnJs0z4Aqr1Rj7O/H6Wi1UrC0qXkXbAAFAqMO3ZgvXsX9z59sFy7hunoUTyGDEHo9XhPnw6ALTKSuClTQKXC51O5DNmSk5ny3nxuX75N9UbVWX3kG3m46tjFqWn76o8vGNJy2DPz/qlMxhQiHz7i2yPfYDIYWTQ2DZ/95R+fM7RltvoPAbAYU4gLjc4RDwWVZz6siZkj2Z/H3+HcvjNUblyNJYeW2ct+2m9yzvZPmNR6NDo3LeNWTc5Q9v9IDVenXQOO/naYYPUdvGYsBIUC0+7tWO/fRd+jL5YbVzGfOIqubSfUlauBVfZYSVwsj1dRla2Ivms3sFrAJpH45Sd4TZ310p0o/yIS4x/TM/0YXjUJIayk+U4LYLIkSduy2qdL4Tdy5CRnaF66XyotrpSXs1xMr35GF23vL6FlupzzF5iUg7+R1cqcYxJNCYnMsbjevfWKspIUmXfMv4heVVbS5+VzjpXku+3gS1+AhsFNs32/ORS697/px/CqSZIk5f/vNOQqV7nKVWb6bz1qu9Z/rmLIVa5ylatXWa9yp3J2lVsx5CpXucpVDiq3YviP6Nv2OdPQ3W1Lzg3i2jQ+53yaf54Tn2NxAawZnXPe1uVnZm8UUnZ08aM6zw6UTTWfm3O+1jt7uOVYXMIrUyfd55b54oNnB3oO5WS/wNozi58dKJvyLNAox+LKid41aw76dv//0v9ExZCrXOUqV/+WXuWJa9lVbsWQq1zlKlc5qP/aSE9X+p+oGJRlqqLrNBAUCszHdpGy5yeX4VSV66HvO4mkBaOwPZA5Oor8IejeGg46PZ8NlRjTbjR9JvehWuPqmAwmlo5dwq0skMgffD2VwEKBDG8uj2Ov16Ye3UZ3Q1+iIKYf5mN7dB+AP+/FsODwdWySRIey+elbLcQprl03Ill28jZCCEr6ejDn9fKoG3alfduyWAwmjo1eQezfd53286kQQp0lg1DpNITuO8/pqTIuoeLYThTv1ghjrDwp7vycHwjbdwFF4XJoXnsTVCqEmzfmo79iObs7LT/L1kFTvzNSkjxRynx+P9ZL8qQidf1OKEPkCVHmk9uBk3w4ewKNmtXDaDAyfsRHXPrrqlMa1WoV0+a9T+161bHZbCya9QV/bN1LjTpVmTprHKXLlsC661ust86l7vOieZaZRn08nDpNamE0GJk1ej7XL95wCvPZj4vxC/DFZJRxIqPemSDnSckqaN/oC0KB+dQezAd+cXkMZYU66HuMJ/nT8dhCb4FShbbTYBTBxUCSSNm7AaFSo2nRA4QCy/mDmI9tdYhDVbE+miZvY0uUh2laTu/Bcj6dna9Gh37wXFRHD2I+dwx9z+GgUJKyfxum3xzhfZpm7dA27wA2G5LRQPKqRdhC74FSidvA8ShDSoBSScrhXXB0W46hslV5C4BkwxIX6rQ/PD/Ce9Gi6bRs2ZjkZAMDBozl/HlHPpaHhzt796b97oODg/j++18YP3566rqOHVuDPKioBuCIKn4O5fYxuJDdBMIjw7pSwHIgD6AFDgObgXn2IMWBUMAA/CVJUk/7fkuBLkBBSZJsQog+wEj7PmWBa4AV+CMLxrhS13UIyV98gBQXg9u4T7BcPIEtIkP7q1aPumE7rHfT3bQUCnTvjsX43WJsYXeYfMCTyvUqkz8kP4MaDqRUlVIMmTWUce3HujxwnZZ1nJDI967dY/bA2XyxLm0fq01i7sFrfNW+CgEeWrr/cIrXivhRzCctG+/FJfPNmbus7lwdL52a2OQUFIXLociTj1/rjMWvajFqzunNH22nOaWj5tw+nJjwNdFnbtJ43XjyN65I2P6/ALiy8g+uLEvDRgiFQNP4HUw/L0HdoAvKQm7g5sx0slw/jfmAI9VTEVIehX9BjOtnyje8ruNo2fYaIUUL0aRmeypXq8CMBZPp9HpPp/iGjelPTFQsTWt1QAhBnrzybPOwh+FMGP4R/Yf1pE26ZLxonmWmOk1qUaBIMG/Vf5dyVcswbs4oBrZzPSlt+vBZXP3retoK4YO2wwAMq6YjPYlBP3w+lsunkB49dNxRo0NTtzXW+2n7qmvKPiyGJaMR7t7oBnyI0Llj3DAPKT4WXd/pWG6cRYp25AFZrpwgZadrHpLmtc7Y7l0DQN9nJEmzx2OLicJz1jLMZ47KN367Uv7cS8qe3wFQVauL/t2hJM2diLpWI1CpSZjYDzRavBaupmFXQyoqu3iVkvSbOZipHSY4HX/psAWpVNRRyyZSu01djv1+hE+HL0wNs+7qarBl3hbfoXVzunV+g8kzFmYa5qlef70xxYuHUK5cQ2rWrMKnn86iYcP2DmESE5OoVatV6vLRo9v49dcdqcseHu4MG9YH4MQzD/gM/V94Y/i3kBifAp/YGUdlgM8kSdppX66MXDt3ty8/rRQUQEfgAdAQQJKkb9PtEwY0ti9nZTxR0xYVjhQTCVYLlrOHUFWo7RRI26YHKXs3I6Xj4ShLV8UWdhdbmGwGkxCXQM3mNdm3WZ5Fe+3cNdy93MmbCRK5w4AObPpsk8P6hzcfEnrb8SnpYmQ8Bb31FPDWo1YqeL1EAAduO07A/OVSKG9WKICXTg2Aj5sGZdGKWK7I5Tj67C003u7oMyCV9fnyoPbUE31GfgO689MRCrbM3A/ct0oxpCePUPgHIz2JwhZ5D4Vv/kzDp5fCNz/W0BsyMsGSghT1gG69u/DLD/IT7/kzf+Pl7Yl/gDP9sku39ny19BtA/mE9jpXfRkIfhHP18g1sGW4iL5pnman+63X54yf5rejS2St4envg6wKb7fK8CxbHFhOOFGsvYxeOoCpb0ymc5vVupBzcAua0CkrkK4j1plxJS0lPQJKQkuOR4qLAZsV6+TiqklWzlQ4ARWAIwt0b652/Ed4+2CLCsD0KB6uFlGP7UFd3RIuTHkmt1aUj2UnyskKB0GiRLGbK1iqfI6hsAIXGA5spMdPzeB6Ed7t2LVi/XjaAOnnyHHnyeBEYmDnsr1ixEPLl8+XIkbSBER99NI5Fi5ZBDvQ/57KSsq8gIPXxSZKkv7MI+1SNgYvAV8A7L3HsYFtc2ggUW1w0wtsRh6woUBSRxw/rpVOO6/PlByT0Qz7GbfwSOg3ujG+gL9HhaTegmIgYl3jlHuN68MuKLU54ZVd6lGQkwDNt9myAh5aoJMf97sUlcz8umd4/nabnj6f4814MCvc8SIlpsz6TwmLRBzr+UPWBeUkOj800TKk+zWmzZza1Fw9A4+2GW2BepMQnqKq3xHxiK1KKEaHRO6VZVaIquu5T0bQZiPCQ47NFPUAZUg5UatC5oyhYioCgfISHRqTuFxEWSWCQ44/W0z4SZ8ykYfy2bwOffz0fP/+sb8ovmmeZyT/Qj0dhaRTWR+FR+LtAXQNMXjyB1btW0HtUDwCEty9SXFrc0pMYhLdj+hX5i6Dw9sV69YzDelv4XbkSUSgQefOh8MuPlJJ2HlJ8LMLT+earLF0Dff+ZaDsNR3g+PZZA0+wdUvbKb3JCp8MWk3ZOtpgoFHmdz0nTvAOeS9ah7zYIwxoZf2I+cRDJZMTrq814fbYR09Yf8PTxzBFUdumaZWVfB1vOkATy5w/k4cPw1OXQ0Ajy53dlkyzrrbfa8+OPv6cuV6pUjgIFgtixY2+OpMcq2bL9eVX1b1UMnwD7hBA7hBCjhRDZGQ/5DvA98AvQVgihfsFjZ833FQJtxwGYtnztvKdCibJoWYxrF5K8ZCJ1Xq+Dl4+3i+gca/4iZYsQFJKf4zuPOYV9UVltEvefGFjZsSpzXi/Px/uuYHH1ypphnWsDcDnM9TV7+LXOGLY1n4IhMo6qH3UHIVAEFMJydg+YXVdq1tt/YfhmMsb1M7Ddv4rm9d4A2O5fwXrnIrq3JqJt1R9b+G2XLOWM+aVSqcgfHMiZE+d5o0k3zp3+i0nTRz87U54hV3mWYDK7DOsaA+2c9ukjZtOzWX+GdhxJpZoVadmlueuDp99VCLRt+2DattopmOX0XmxPYtCPWIC2XV9sMRHOeZZh0XLjPIbPx2BY9QHWu5fQviF7yauqN8V68wJSQlYEW+dzStm9hYRRPTBsWIGu47sAKIuVAZuN+KFdiB/ZDW2brmj1zuiPF0Fl132jAVJK5m8LzytXRTyr5pyuXd/ghx9+s+8rWLDgQ95/P3vOc9nRv4XdFkL4CCF2CyFu2P+7NNoQQhQSQuwSQlwRQlwWQoQ8K+5/pWKQJOlboAzwI9AIOC6EyBQWJITQAK2BLZIkxSO3+7V4nmMKIQYKIU43a9bs43BVWruzIo8fUny6H45WjyKoEG4j5uD+0dcoQ0qhHzgVRcHiSHExWG9eRFW1AW6jF5CvoPyk6xeU9tTlG+hLbAa8cumqpSlWoRir/vyaeZvnk79IfmZvytxoLp+7jsiEtDfYyEQT/u6O2ZPPQ0ejIn7oKzei2MCPWffDT8THxqQ+rQO45/fBEOlIzkwOj8UtyMcxTIQcxhgdj2STQJK4uX4/fpWLkhwei/DIi7pBJ3R9Z6EMKYciXyFUlRqlRWpMksFjgOXiYRT50qwULad2YPn7CMLNE2VIecJCIwkKTnt6C8wfQGSE4xyCx7FxJCcZ2LlNbqLb/utuylV0dKN7mTxTKxUEe+kJyevG/bi0Pp9OvdqzetcKVu9aQXREDPnyp73J5AvyJzrS+Q0jOkJ+Yk5OMrB7y17KVi4jvyHkSXtrFN6+zmUssBD6gTNwm7gMRaGS6HpPkjucbTZStn6LYelYjGvnglKJUKc1eQkvH4e3QgAMiWn5f+4AisAQAJTBxVFVb45+2CI0Td9BVboiqvJpzVAKX39sjzN/azKna2rS1GuK+cJJNE3a4TFpAcIrD5LNliOo7Jot62TZjJQdpUd4h4c/okCBtHlBwcGBhIe7ZmFVqFAGlUrJuXNyo4Wnpwdly5Zi165NXLv2J0BtZC/lzNtbnyGbJGX785J6H9grSVIJYK992ZXWAgvszfg1gUeZhEvVv4bdliQpTJKkbyRJao/skpQV97wl4A38LYS4C9TnOZuTJElaIUlS9T179lQoWKQYwicAlCpUVRti+Ttd/5IxmaTJ3Uma3o+k6f2w3r2GYcUMbA9uYrlyBkX+EMzH95C8cBT3r9/nzIHTNOncBIBSdoR3Rg+FHet20LtGL/rX68fEzhMIuxPG5LcmZZrWcgGe3H+STGi8AbPVxs4bkTQq4vjK37ioP6cePsby9yHCv53Ou291QXH3b1RlZA8Ev6rFSIlPxpABqWx4FIcl0Yhf1WIAFOlSnwc75eaM9P0RBVtVJ+7aQ2LO30YyJWP6aTHG1R+CyYDlwgEsFw6kRermlfpVWbQStlj7a7wQoHPH8tcBTDu/RUqMY903m+j4ZlsAKlerQEJ8IlGRzgDLvbsOUbu+/Fus27AmN685j3Z50TwDeGxI4V5cMsFeac1iP6/5ld4tBtK7xUAO7TyS+vRfrmoZEuOTiMlw01MqFXjnlc9dqVJSt1ltbl+7g+3hTRS+QYi8+eQyVqk+1ivpmiWNySR93JvkeYNJnjcY2/3rGFfPkUclqTWglis0ZYlKYExCeORBePvJb6xla2O5fs4hHcIj7a1VWbIqthi5Y9r06zIMn4/G8MVYUvZ+T8qhnSBJKPwDQalCU6cJ5jOOaHFFYBqSWlWlNtaIp05okajKVZHfJqaNQIqL5dTO4zmCyg679TDVUvNFlR7h/dtvO+nevTMANWtW4cmTBCIiXN/73nyzferbAkB8fAIFClSmVKl6lCpVD+A48AYvMSrpXzTqaQ88ZcuvATpkDCCEKAuoJEnaDSBJUqIkSckZw2XUvzJcVQjRErlmMwshAgFf5FFImekdoL8kSd/b93cH7ggh3LJzUhlkMf60DLehH8vDVY/vxhZxH03r7ljv38B6MYuZuYYkUvZvwW3cYpDg1m+n+f6T7xk8YzArDq+Uh6uOW5IafOmOTxnZ6r0sE1P79ToM+ngQinzeaNsNxRb1EH77nIkNSzH013PYJGhfNohivh58eeIWZfN50aiIP3UL+XDsfgyd1h9DKQSj6hZHH34V25NKtD+6CIshhWOjV6Qep/XuWWxvPgWAE+9/S90lA1HqNITtv0DYvgsAVPngbfKWKwySRNLDaE5M+AbJaiNl/0a0HUeCUMidqsnxqGu3w/boHtbbf6Gu0gRl0UpgsyIZk0nZtVo+qEKJrus4AKQUI6ad37B35yEaNqnL/lO/YTQYmfDetNQ0bt2/kbaN3wZg3vSlLP5qJlNnjiM25jETRsjhKlYpy1drFuPt7YVGYUWq1QbjhpmoFIoXyrM8etctksf2nqBOk1r88Oc6jAYjs8fMT922etcKercYiFqjYfGG+ahUSpRKJacOn+G39dsY0s0L06+r0Pf7UC5jp/Zii3yApvnbWB/ecqwkMkh4eMv7SRK2JzGYfl2Owj8Y3TsTQCGwXDiEFB2KumEnbOF3sN44h6p6C1QlqyDZbGBIxPT7SteRSxKG1Z/iPmk+KBSkHNiB7eFddF36YLlzDcuZo2hbdERVoRpYLNiSEkj+SkaVm3ZtwW3wRDwXfAtAysE/2LX2D4JLFMwRVHbxMa5x3E/1PAjvP/7YR8uWjbl8+TDJyQYGDhyXuu3EiR0Oo5G6dGlL+/a9sjz2yyoH3gSyqwBJksIBJEkKF0K46nEvCcQJIX4GigB7gPclScqyZs5x7LYQwoY8YuipFgMFgDak9fgvkCRpXbp9DgDjJEk6LYRwQ+6oDrE3Iz0N8zOwSZKkTfblu0B1SZKeyU9PeK9tjpxkty05EYusTeML5VhcOY3E6DTBPcfienWRGM5zKV5UO3vkHELkVUZiDDnq3L/2onplkRjG+y+NwS7hXy3b95ub0WcHAQPTrVohSVLqE54QYg/gqid9CrBGkqQ86cI+liTJoZ9BCNEF+BqoAtwHNgHbJUly0amaphx/Y5AkKbPmqUxBK5IkNUr3PRlwGuogSVKnDMshL5bCXOUqV7n65/Q8o43slcCKLLY3y2ybECJSCBFkf1sIwnXfwUPgnCRJt+37bEHuR8myYvhPW3vmKle5ytWrJkmyZfvzkvoNeNou1gv41UWYU0BeIcRT++MmwOVnRZxbMeQqV7nKVQ7qX5zgNhdoLoS4ATS3LyOEqC6EWAVg70sYB+wVQvyNPHw/k06pNP3nrD1fRDll7bmyes615bc/nrNGdMvdcs4qdOyz5+RlW5sX1MqxuHpOOJtjcS3Ol3Pj6Mc8yrl+gWjr846tyFxGKeesaAG2Vs65CVnBe+/kWFwJDw/kWFxqv6Iv3cdQyKdCtu8392P/zrX2zNU/o5ysFHKVq1y9nF5l1EV2lVsx5CpXucpVDsqaBRzwv6LciiFXucpVrnJQuUY9/yH1nTaAKo2rk2Iw8fm4JdxxwZGfsmYaee0c+SsnL7Fq6nJsNhuFy4QwcPZQvHw12ExGFJ5egMC0dxumXzY4xKFp8Qa6lh3kyUdGA0nLFmJ7KGOOlYWL4jZoLMLNjdWJEgPbDGXwlIHUblILk8HEnEw8AJ5qzrczCCoURO+m/QEoXq4YY+eOoohei9DpEBo1WCzE/bCTmBU/Ouyrr1GewCkD0ZYqQujouST88WfqtnwT+uLRqAYoBEl/noMPljNo+iBqNK6ByWBi8djFWXpOfPj1hwQWCmRo86EAvDv2XWq3qI3NZkPjCykntoAxkT9vhDF/+xlskkTHqsXo27CcQzwLdpzh1B0ZZWA0W4lNMnJkclen4/WZNoCqjathMpj4YtzSTK7lR6meAFdOXuZr+7UMKVuEAbOGEOChRGi1CI0GyWIh6dftJKxxxIh7dOuCR/vWSFYrtrg4Yj9egNU+o7bA8V2Yb8nt5BPvxTKv/6wcSZdCq8JqsRJ2L4ySFUtgNJiYN3oBNy7ezDT/Z37zMfkLBdK3mTwc/sMvp1CwWEFsSHh6eaBz05EUn4TRYGTG6Hkuy9gXP36Cb4APJqNMfh31zngex8RRuVZFRk0fRrEyxUj5aT3a+o1AocC4axvGHx3LvrbVG+jadpQnPhoMJH22EOuDe6hKlsZ9xNNJZwLDhtWw906OeSio/YpiiXuIZHGNVX9eb4eX1f+Fftt/pGIQQkjAOkmS3rUvq4Bw4IQkSW2FEL2BBTjOfu4GJANXgKuADkgAvpAkaY0d/HQEKCSlG+clhDgPDJQkKdOZVFUaVyOoSH5GvDaIElVKMXDmECZ1GO8UbvGweanI4HHL3qdOm3r8+fthhswbwdpZ3zBaOoH3qs2k/Lkfw5ov8Zy3DPOpP1Nv/AAph/eQskuecq+uXhe33sNInDkBFErcRk4heelsrPdu8d61vFSrX40CRQrQrX5PylYtw5g5IxncbrjLc2jYqj7JGbwdhkwZyOrF39H31N8UP7wWc9gj7nWbQJHNS0jYd5yUm2kTnCxhjwibuBiffp0d4tBXKYO+allut5W9BwpvXECXIV0IDgmmf8P+lKpSiuGzhjO6vWuoXd2WdTEmOZKKf1r+E98tkr0CtmwZgbrcaxhP/c6cradZ1qsJAV56ui/fyWulC1AsX9qkqfGtqqV+//74Na6GZ2AE8fRaBjHitcGUqFKSATOHMNnltZyfei3HLptI7Tb1OPr7YXpM6sWPSzfS8+oR8m/biCU8kkcDRxOw5ksMh45huZN2Lc3XbhLZcwiSyYR753bkeW8gMZNl2JpkSiGy+yAA5j3yyLF07dl7hJ6jetC5X0faV+hMmaplGD3nPYa2cz2jvkGr+hiTHcvFx0NnAXLn85yV0ylWuihvNpB9JibMGU3/dkNdxjUto88EEBEayYzR8+g++C1ef70tT8YNxRYdhfcnyzEf/xPrg3Rl/8AeTDvsZb9WXdwGDCPhwwlY7t3hychBYLMi8vqQ5/NvaH02NMc8FGzmrEnZz+PtkBP6v9DH8E8NV00CygshnoJpmuOMwNj01FvB/nk6tvaWJElV7MCnt4HRQog+kiTdRfZmaPA0AiFEacAzq0oBoEbzWhzYvB+AG+euPTdHPn/RYC6fuISyeGmsD++hrlAVLBbMR/ahqZE53x5dGt9eVbk61ru3sd6Tn7zjH8dTr0Uddv60C4DLZ6/gkYkHgN5Nx5sDu7B26XqH9ZIk4e7phr5iSayxTzA/iACzhfhth/Bs6jhL2Bz6CNO1u7JXgmMkCK0aoVYhNGqESkXx8sXZu1lGED/Lc6LjgI58/5mjK9jTfAQQKhkId/FhDAV9PCjg44FapeT1CoU5cDWDkU067fj7Hi0rFHZaX6N5TQ6mXsvruGfzWj69DpIEbh5uaMqVxvo4DktoOFgsJO/ej/61ug5xmM6cRzLJQ7RS/r6CMp8/mSmn0gVQsXZF7tsr9Stnr+Du5YGPi3Khc9PRdUBnvstQLtKr5ms12LxWHt5+6ewVPLzds+0zARDxMJJbV27jldcL2+NYbBFyfpkO7UNdu75DWCm9t4NOnwZyNZlS2UhCowFJok2b5jnooZD1jfh5vB1yQpIkZfvzquqfbEragYzB+Ik0hHaDLPfIWzqbcwAAGndJREFUIEmSbgshxgCLgG/tcbwNPPUxfNu+Lkv5BvoSE5ZG9IyNiME3wNcJAAbwwdppFK9cknMHznB8uwwce3D9HjWa10Lhk4JQa1D4yQXYFhuFskRZpzi0LTugbdcVoVKTME1+0lYGFQQkPKbOR3jl4Z0NB/AL9ONRunRFhUfhF+jnBG/rN6EPm5b/iMng+GT02UdfsnDDXHzddCi0Wh4Mkl+xzRHR6CuVela2AGA4f5Xk439R4ug6EILH3/2OrlRRosLT0hUdEY1foJ8TLPDdce/y84qfXXpO9Bzfk6adm6J0lzDtX8OjBAOB3mmojQAvN/5+6JpmEhaXRNjjRGoWDXDa5hPo6+AJEBMRjU8m13LK2mkUr1yC8+mu5eqPV/HB2mnkddcgtFqix3wAgDUyCk35zImu7u1bYTyadlMSGg0Ba75Eslqp8emWHEtX9ym98PbJw+z30mi80eFy/sdmKBd9x/fmhxU/YczE86NyrYpYrVaunE/Df0SFR+PvoowBfLB4IlabjQPbD/HtEkd3OJ1eiy3+SeqyLToKdSnn/NK26YC+45ugUhM/eVTqelWpMriPnIgyXwCJi2YTVLWxSw+FzOB3/7SHQk7qX2Ql/WP6Jye4bQTeFkLogIo4W+a9JYQ4n+7j7AYj6yxQ2v79B6CDvWkK4C37cbLWc/DaZ/acxoAavVBr1JSvWxGAL8Z/SsuerdG/OxCUKiSLOX1ETnGY/thC/LDuJH+3HF1nmW+PUomqdAWSlswiYcoIGrSqj3c2vB2KlytGcEgwh9P1CTxV+57t+HzaV0R8+AWGC1fJP3tk2sZsFk51oSC0xQtyo0FPbtR/F7c6lfDM4/x0lTFdRcsWJX9Ifo5l4jmxdsFaetXuhfXe36iK13SZHNdeEbDz73s0K1cIpcK5eLrcJ5NzndVzGgNr9HbwBGjRoxWrZ3zN47lLSLl4GZ+p454Zj1urZmjKlCT+ux9S14W1e4fIXkOJmTqb3h/2Q+vm7FXwIul6q2Z37t24xzvD3s4yrmJlixEckp8jLsrFUzXv0MQlOtxVsqaNmEWPZv0Y0vE9KtWsQKsuz6bcuzo707YtxPXvRvK3y9G/lWbharl2hSdDe/Nk9GD0XbujVDrP4/n/6aGQk8o16slCkiT9BYQgvy1sdxEkY1OSwUUYSHdblyQpArgENBVCVAbMkiRddLXT+vXrN1y9ejX56tWryfce3sc3f1ozgE+gr9PTV3qZTWZO7T5JjRby5KywW6HMePcjkpbOQkoxYouQGYEKH3+k2MwZfuY/96GpKb9u22KisFy+gKZeYzxnf0FQwQAEkC9duvyD/InJ8EMuV60spSqUYNPx9Xy+ZSkFixZg6Y+LAGjZtQUHtx/GEhGNZLGis78lqAP9sGRxfunl2aIuhvPXyNOxGSEbF6ApEIBCocA/KC1dfoF+TukqXbU0xSsU59s/v2Xh5oUEFwlm7qa5TvFb7/2NsmAZArz0RDxJSl0fGZ+Mv6frZ4E/MjQjKYvXQNtiEAu2f0JsZKyDJ4Cviyfp9DKbzJxOdy0bdW7MiR3HsD6S80xTVn7mUAb4Y412volqa1bFq083osdOhXS2r7boGDy6tsdv/jTcPN2wWW0vla5mbzeny4g3WblzGdf/vkFIybTz9wvyc7rBl6tWhpIVSvL9se/47JdPKFC0AJ/8v/bOPEqq6trD3+7BZjZOQUUFEbUFIwr4BPWpkDgxKEMMAg6gUYxGEYVoTIwvDtGIik8URcU4D0Efo6AYQFBREUUFBAQRUQyTEu1G6Ibu/f7Yt+nbRVVRp/r2QNf51qq1qu+t8+tTVbfuPmefffYeZz70nhefw2OvP8I5/bvx+aLlNA3VmdjvgH3ZGCft+YZQnYnpE2bQ+tj8Cue3bikiq0n5QCZr3/0o/S7xtV88ZwZ7dKroasrr1pNGf7iZ7EOaU1RUFFkNBcnJI7vx/jvcljVNXXAlVXVKjEnAPaTg7knCcdiCdBll7qSkbqQBAwb0z8/Pb5Cfn99g6azFnNanMwCHBzUUYqf49WLyyLfr3J41X5gPvMk+9oMo+WIZOS1aUfzubMjJIffkLhTPj8lvf0B5fvvc9h0p+bctrWz/eB7ZzVtSNHMaBX8YzJfLVvHerHmcGYzMWrc7is1xagBMfHoyvdv3pW/HAfy+5xC+XvkNQ867HoDv1n3HsZ3asmXh5+QdeSjb1qyD3ByadDuFghnv7fqTBbZ9u4EGxx/Nphen8mXvaylavpr5s+fzyz6/BKzmxOaCzTu5kaY+O5ULj7+QQScNYlifYaz5cg039rU6IQe2KK8RndXsSPTHjbRptg+rvy9gzaZCtm0v4fWFX3FqfjNiWbXxR37cWkzbg8tvsiUrPqBo+hiGdx3KB9Pf49Qd32X8mgA7f5cddnyX36//ntYdj6b4s6XscXhLtq9dBzk5NDi9M1vmVPwuc49oxd5/HMrG62+mdFN5nQtp3AhycykcN5ENVw6nYFMB70+bW6l+rV+znn/cOpbLzryCtavXUrLNfPJHtTuKzQWbdzIyk56Zwnkdzqdfpwu5utdQvln5DUODlOcTnprEo3c+zsIPFjN9/Iwdo/82Ca6x2DoTJ/2qEyuXVdyZ/MP3P5C1195kNd0fcnLIO6UL296vOFvJOjB07R/fidJv7b1lNd0fsrIpenUCBbf+Cf3pJ15+eXJkNRR0exElBWsTRiVVN9VYqKfKqOpw1SeAH1R1oYic5to4iES6BxgVOvwK8DcsgqlLKjofzZxPu87teXDOGIq2FDE6lEd+xNT7Gd71WvIa1OPGx/+8I4/8wrmfMv1Zi4A4+ZxTOOuirjSpV8q2BfPI+1U38s7oQfHMaZR+vYp65w+iZMUyts2fS97Zvcg9pj26vQTdXMDmB81XrJsLKZo8jiZ3PwIKn0+Zx5P3Pc3QO67hhXeeoWjLVu68bsSOfo2dPoZLzxic9H3dPfw+rrn1Kprn5lBa+BPZjRpy2Gtj+M/L0ylesZp9h1zA1oXLKZz5PvV+cTgHjb6Z7CaNaNT5BPa75gJWdv0dBa+9TcNOx9Dy1dGgUDjnQ5677zmuvO1Kxr41lqItRYwcNnLH/xw1bRRXn3110n4NunEQzQ5rhpYq2U2KKf7wVXKys7ixWwd+9/QsSkuVc9u1pNXPf8boGZ/SutnenJZ/EADTPl3FWUc3T+hm+mjmhxzXuQOj5jxC8ZYiHhpWfmmMmDqS4V2Hktcgjxse/9OO73LR3E+ZHtQEGHPDQwz6n9/SNO8SSgs3k9WwIQeM+weFk6axfeVXNBk8kOIly9g6511+NuRypH599rnrLwCUrF3PxutvJvfQQ9jrj0OhVCFLGPvwK8x86V8cfGTzSvfrouxLKC4q5oPZ83n27aco2lrE368rj6Z57PVHuOzMK5J+/gBdzunMGxNnMHfGe5zY5QTGvfMsRVuKuP26v+94zVPTH+PiMy4jd489uP/5EeTkZJMV1JmY+NyrABzV9kjuGnsbjfdsBJTyszHPUrpxPUVvTKVk9SrqX3AJ25cvZdv7c6nXvTe5x7aHku1oYSGF99m1n9P6GOqf19+qzpUqhaNH8s9/TuLEE4+vlhoKLrUdoqAu7GOoklxJIlKoqo1ijp2G1VxIFK56JVbHITZc9eGgNGhYayJWpKJjKv2p67mSok6J4XMlueFzJblTl3Ml1a/fPOX7zZYtX2VOrqRYoxAcexN4M3j+JPBkguaJFqHDWufu6jUej8dTE9TmtYNUyZidzx6Px1MdlNbiaKNU8YbB4/F4IqQuzBicQqvq8gNLq1GntWpz37xW3dCqzX2L+n3W5Yev4FbO5bt+yW6vFbWe1/JaVa1XW7XqNN4weDwej6cC3jB4PB6PpwLeMJTzaAZoRa3ntbxWVevVVq06TZVscPN4PB7P7oufMXg8Ho+nAt4weDwej6cC3jB4PLUYEUmYiElEDqvOvngyB28YajEikisix4lI4pqHnrrOJyLym/ABEaknIrcDr9VQn6oEEflbhFodotLKRDJy8VlEeic7r6r/56B1UbLzqvq0g9YjwChVXSwiewLvAiXA3lhm2pTrWojIZcCbqrpcLIf1E0AfYBUwUFWdUpWKSB9VfSXO8T2AG1T1NgetB5KdV9VrUtTJV9WlwfM8VS0KneuoqqkVpUisvw9wCrBaVT9Mo31n4GqgrM7qEuBBtYSSqWocBjyIpa/5HdAGS0U/AfirqjqniRWRo4E/AK2xQmyfAfeqFdeqNCKyL/CdOt5cROQjVW0XUR8WAI2wmi0vanlNeU8KZKphKAU+Dh5QsfinquolDlqj4h0GegDNVDXlfFQislhV2wTPrwVOU9WeIrI/ME1Vj3PQWgQcp6rbRKQ/cD1wBlb46BZVdaq/LSKvA6XAlar6ZXDsbGAk8JqqXpusfYxWMbAIK9X6LTHFV1X1qRR1dtxIYm8q6dxkRGQKcKOqLhKRA7CysvOBw4BHVfV+B61u2A391kBHgHbAn4Hfq2q8qobJ9IYDdwJrgTNVdbFL+5DOuZhhuRN7bwK0B/6IDT4mOup1BO4CvgduA54B9sW8ERepasqzGhH5BDiNuMV4QVVTK0tYrnckVtCrL1BMuZH4ykUnI6npnBw18QB6YbWi5wM3A60i0hXgAmAh8BJwjGP7BaHnr2Ij+53Opaj1cej588CQ0N8fpfn++gFfYDeA8cDbQNs0dPYBrgBmAW8AvwX2SkNnQbzn6XxeQZvFoec3AU8HzxsDnzpqvRnvs8Hqn8920MnBbtorsJQOE4AZwJFpfoefAC3iHG8BfJKG3nxswHEesAnoGBzPT+OaLQJWAl/GeaxM5/2GtNtixvAL4J3KaGXCo8Y7UKNvHhoC/YGJwU3u1DR1coKb2xKszkS6P9pZQHdsVP8fYP+Q/lJHrY+AA7CCR+uANqFzS9LsXzZwO1AIfAMcEcF30AwYhs0cLnR9j/Gex/s7Rb2wMZ0BnB/vXIpaCb8vl+8SG2Q8COwZOtYdK2Z1Zxrv8bN0zqX4mS2JOedqGJyNeYq6WcDpmDt1LTChKv5PXXpketrtrcAPwI/AIdhN1AkRuQoYgt1IztLKTVMHAw8A+wPXqura4PgvsRmEC3/BRnPZwCQNXA8icio2KnNCRE4GRgPvAAcDpwKTReQl4A4N+fcdNNths5DTgWmAqx//oGC9QkLPCf7euaD0rvlaRK7GjF47gsVdEakP5DpqbU7zXCwDNWZ9Q1WniMi/MLeUK9tE5BBVXR0+KCLNgXRKvoWLD2yJOVejfmoR+W/s+uqJuS5fBIaq6g812a/dgUxdY+iMXTD/BfwL8zvOT1OrFFgPbKDiD0Gw9YpjKtndtBGRHKCxqm4KHWsAZKtqgaPWfGx9YV7oWEPMAJ2rqvkOWn/FRr1LsB/ra6rudShFJGkhYE1xrSKk93NsTeAA4CFVnR4c7wy0V9V7krWP0foPMCfeKeBkVd3LpW9x9E8C+qvqVY7tegJ3Y3XTP8Su2eOBG7EgggmOeiWYoROs+mJZbVIB6qlqygZVRAaqVXeMPV4P6KGq4xy0vgZWY9fXP1V1XaptPZlrGEqBTzH3kRIzstEUo2ICrSuwkWW8D7Kvqt7toDUqRkeBjcAsVX07VZ0E2gJ0xlxnPVS1qWP7LNX4palE5ChVXeKgVYrNWspGmGXvucaNaVQEM7OEqOrsNDSPxb6/32B+91dU9cE0dNpiwQhtsM98MXCPqn7iqlVViEg2tnbRDzgTeEtVf+3QvnklZ+8ZTaYahoEkmea6jDSDEdNszD++JuacU2RMghHw3tiN4CV1iIoJaZ6A3Ux6BVpXYa6lTUkbxtf6edC+DeVhjg+p6npHnebJzqf6gw7cWy01CAkWkZex9whwu6rOdOzXZJJfF+e46CX4HwdjaxcjUnz9EVhkTT/gOyyoYZiqJv0Md1dE5BTseu0GzANOwr7jn5I2jK91MebmDYcLP6AOIeSZSkYahigJ4qVHYy6V68LTXRFZoA4hpkn+R31grouWiNyBGZTVWJjeeGC+qh6aZh9OwqKbnsRcEGXhlxcDA1T1nXR0Y/5HNnbTfC7F188ArtYgRl1EFgIDsaCCm1T1LMf/H/koP9DdF4va6YetfYxX1WEpti0F3gIuVdUVwbGVqtoyzb5UufFLFxH5BrteH8YWiAtE5Mt0rtlgf9FQ4DoqhguPAP7XG4fkZOTic8Q/DlXVx0RkNvCciHQFrgpGOJFYXVXdYp4gJy4HlmE/simqulVEKtOfe4GeqrogdGyiiIwHxgAnpCokIk2wmUczYBIWsvp7LDrpYyAlwwA00Yobl5aXLdSKyJ2p9qeM8I1fRPYLjm1w1QnaN8Zmaf2BIzDD3FJVD3KU6oPNGGaJyGuYz9z5YgiR8jpJDfAKtlDcFygRkYmk/xu6EuilqqtCx2aKSB/sM/SGIQkZOWOIcmQYs8kqBwvn7AVcBDzs4kpKoJ8DXAj0VtUeDu3CPtouWCjsr4CD01zo/UxVW7ueS/D6iVjM+7tYxNVewB7YXouPk7WN0VmuqocnOLdCVVulqhVqdwu2W1mwMMft2G70Wx11tmCukD8Db6uqpjPSF5EcVd0eLPT3pPz7fAqbeUx31HtSVQe6tKlOQmth/YCuQBPgUmCqOuzyjvJ6zUiiinutKw/gJMfX7xR7je3eXAkUOGoVYKGzBaHHOmyH8IGVeE/1gF9jI7J1wPNpaCwhziY0zKfvusdiYeh5NmYkGqfRp8lAtzjHuwOvpqE3FJu9HBo61hJ4HQtzdNV6HwuTvAnbPe28SYs4+zGCz3wwMDMKvdr6wEKEe2AuzI2ObT9M55x/2CNTZwzZmP+9GRYquUhEumM/4Prq5svvqXFC/ERkL2Cwqt4VVb+jIHBx9Fb3UM7Lgcswd09ZnqX2wN+BJ1R1jINWpdNXBO1aYfs75sb06USgu6p+7qi3ADhdVTfGHN8PmO5yXYTatsRGv+cDhwO3YCP9lPoW1TpVSG9p0J9EaSeccmhFSbLZjIjUV9XYfRLJtH7CdovvdApz6TVMr5eZQaYahiexTVrzMN/4V0AnLE+OUxx31ASuo7OxlAJgkT+vq6P7R0SuS3ZeVe9Lo2/dseRrbYJDi4ERqjrZUacs9h0qxr+Xhas2cdDKAwZQHim1GFgO9FP3GP9Fqnq06zkH/V8QhJuqakops4MF2YTflev3KCIFwAfENwyqql1c9KIk3QFCAq1IIt8ylYxcfAY6YHmMSoPNMxuxfElrd9GuShGRA7G1gH8DC7Afb3fgPhHprKrfOsg1Dj0fjC0Ql5HWaEBVpwBT0mkbo5NdWY2QVhHwhIgch42EbyGI8U9DrjjNcymhqgtF5GbMeKVKNpYltDILzmFW1OTNfxc0CL7HKGYz9TVJ5l1sMOhJQKbOGCJxZURNMJP5WGP2K4jINdjO26Q7fZPoVtodISJ/SXJa1SHtdlREHeMfM5OpcAr3XbyJIq+ux5LVnZuiTqTXZtSuqSiJcjYjEWfezTQydcaQLyJluecFOCz0N1pzO287xvOxquoDIrKsErpRWP94N8yGWMTIPljG1epmKRbj30PLY/yHpisW5UwGSz9dFnn1W2A4FnnVUx0ir4huplDGDXH/iePGuyoiytmMJHge729PDJlqGNoCTYGvY443x7J81hTJFtecd35GiareW/Y8WMAeAgzCYsLvTdSuiok6xj9KWqrqLwBE5HHMXXmIOuaowsJ5I0ND4a3xNt5F+b9qmNjUMonOeeKQqYZhJLYztoKfMYg+GYmFyNUEe0r86nKCxXOnTLALuOwH0Co8I4L0ZkUisje2k3QAFkffTtNIrREVqjoeGB+K8R8KNBWRh0kjxj9itpU9UdWSYAevq1FAHYvT7IoIN95VBRVmMyKSCxwNrFHHtCtEn3k3o8jUNYZk0ScLy0Z61Y2I/CPZeVUd5KB1OElmRWWuFwe9EUBv4FEsP5JzScnqIDBe52EJDGsywiayyKuI+xXJxruqQKItbRtp5t1MI1MNQ8JdsenumK1tiJWpvElj6viKFUm/RR12UQftSrEKW9uJn168Rm50HjeCNZjzsfWh57EF+zdqiWGIrLStp3JkqivpAxG5TFUfCx8UkUtxLxYTGWKJvxKhqvqMg1yLWKMQiMwXkRaufVPVLNc2ntqHqo4ERoY23k0ADhSRG3DYeFdFhEOCTwfGAajqWnHMFSYik5Kd1xpMFrg7kKkzhqaYb7WYckPQAYsa6VVT+xnE6jHsdBhb82imqikb8kyYFXmiIZ2Nd1XUj1lYIMMabD9PfmAUcoBF6lYMagPmRn0BS01SwbJomplyM4WMNAxliFXmKltrWKyO+furkiCZ2ABsQe4zrHzmTjOAJO1fwHLpxJsVnaGqfaPsr2f3Jrj5nq+qz9ZgH46gvLTt/RpUcxORM7Fr9noHrWxs1tEPOAZLnfKCBiVuPcnJaMNQGwl+oAOxjVDvYwXfnfcw1NZZkadmiWrjXXUjItfGbvx0aJuHGYgRwK2qGm9m7gnhDUMtQkSuwvYHzADuiiKfS22eFXmqH4ko5Xl1IyKrVfUQxzZ5WCW4fkALzBA+oTGVFj074w1DLSKI/FkPbCB+5M9uXwvZU7OEw7EDd0u6G++qFRH5WlUPdnj9U9iAaBrwoqouqrLO1UEyNSqptpJW2U2Px4FINt7VAK4j2AuxfSRHANeEopp8eHUK+BmDx5NB1NaNd0HfCohvAATLluoHstWENwy1iF38MPwox1NpRCRXVbft+pWeTMYbBo8ng/Appz2p4HezejyZRW3JPuupxXifnceTWeyXrOyrplHy1VP38IbB48ksoi4V6qmD+DUGjyeD8GsMnlTwawweT2bhZwqeXeJnDB5PBiEiBwK/AVoBC4Gxqrq9ZnvlqW14w+DxZBAi8hK2+/kt4GzgK1UdUrO98tQ2vGHweDKImFxJOcA8v+bgicWvMXg8mUU4V5J3IXni4mcMHk8GUZtzJXlqD94weDwej6cC3pXk8Xg8ngp4w+DxeDyeCnjD4PF4PJ4KeMPg8Xg8ngp4w+DxeDyeCvw/CtciSNTodjQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = df.columns \n",
    "data_corr = df.corr()\n",
    "sns.heatmap(data_corr,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 回答3. \n",
    "> 如果特征之间高度相关，从特征层面，我们可考虑对数据进行PCA降维从而降低对模型训练的负面影响。从模型层面讲，我们可以加正则项以减少模型的不稳定性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 从原始数据中分离输入特征x和输出y\n",
    "y = df['MEDV']\n",
    "X = df.drop('MEDV', axis = 1)\n",
    "\n",
    "# RAD的含义是距离高速公路的便利指数。虽然给的数值是数值型，但实际是索引，可换成离散特征/类别型特征编码试试。\n",
    "X[\"RAD\"].astype(\"object\")\n",
    "X_cat = X[\"RAD\"]  \n",
    "X_cat = pd.get_dummies(X_cat, prefix=\"RAD\")\n",
    "\n",
    "X = X.drop(\"RAD\", axis = 1)\n",
    "\n",
    "#特征名称，用于保存特征工程结果\n",
    "feat_names = X.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "fe_data = pd.DataFrame(data = X, columns = feat_names, index = df.index)\n",
    "fe_data = pd.concat([fe_data, X_cat], axis = 1, ignore_index=False)\n",
    "X = fe_data\n",
    "feat_names = X.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 第4題"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(404, 21)"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 換成 MinMaxScaler 去量纲\n",
    "mms_x = MinMaxScaler()\n",
    "mms_y = MinMaxScaler()\n",
    "\n",
    "X = mms_x.fit_transform(X)\n",
    "y = mms_y.fit_transform(y.values.reshape(-1, 1))\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=33, test_size=0.2)\n",
    "X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "### 最小二乘线性回归\n",
    "lr = LinearRegression()\n",
    "lr.fit(X_train, y_train)\n",
    "y_test_pred_lr = lr.predict(X_test)\n",
    "y_train_pred_lr = lr.predict(X_train)\n",
    "#fs = pd.DataFrame({\"columns\":list(feat_names), \"coef\":list((lr.coef_.T))})\n",
    "#fs.sort_values(by=['coef'],ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of LinearRegression on test is 0.6939789810509471\n",
      "The r2 score of LinearRegression on train is 0.7549146436868177\n"
     ]
    }
   ],
   "source": [
    "#测试集\n",
    "print ('The r2 score of LinearRegression on test is', r2_score(y_test, y_test_pred_lr))\n",
    "#训练集\n",
    "print ('The r2 score of LinearRegression on train is', r2_score(y_train, y_train_pred_lr))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of RidgeCV on test is 0.6961684813070346\n",
      "The r2 score of RidgeCV on train is 0.7548524440445559\n"
     ]
    }
   ],
   "source": [
    "# 岭回归\n",
    "alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "ridge = RidgeCV(alphas=alphas, store_cv_values=True)  \n",
    "ridge.fit(X_train, y_train)    \n",
    "y_test_pred_ridge = ridge.predict(X_test)\n",
    "y_train_pred_ridge = ridge.predict(X_train)\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print ('The r2 score of RidgeCV on test is', r2_score(y_test, y_test_pred_ridge))\n",
    "print ('The r2 score of RidgeCV on train is', r2_score(y_train, y_train_pred_ridge))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of LassoCV on test is 0.6953719445869475\n",
      "The r2 score of LassoCV on train is 0.7546505272258799\n"
     ]
    }
   ],
   "source": [
    "# Lasso模型\n",
    "lasso = LassoCV()  \n",
    "lasso.fit(X_train, y_train.ravel())  \n",
    "y_test_pred_lasso = lasso.predict(X_test)\n",
    "y_train_pred_lasso = lasso.predict(X_train)\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print ('The r2 score of LassoCV on test is', r2_score(y_test, y_test_pred_lasso))\n",
    "print ('The r2 score of LassoCV on train is', r2_score(y_train, y_train_pred_lasso))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 回答5.\n",
    "> 以上三个模型的性能评估分数如下：  \n",
    "> The r2 score of LinearRegression on test is 0.6939789810509471  \n",
    "> The r2 score of LinearRegression on train is 0.7549146436868177  \n",
    "> The r2 score of RidgeCV on test is 0.6961684813070346  \n",
    "> The r2 score of RidgeCV on train is 0.7548524440445559  \n",
    "> The r2 score of LassoCV on test is 0.6953719445869475  \n",
    "> The r2 score of LassoCV on train is 0.7546505272258799  \n",
    "> 最小二乘线性回归在模型复杂度较低，误差较小的情况下有更好的拟合效果。但如果当中有的相关程度很高的特征时，模型容易发生过拟合，这时候我们应该用岭回归来抑制过拟合的情况。  \n",
    "在题二我们可以看到有部分特征的相关程度是较高的，所以在这里，岭回归的表现比最小二乘线性回归在测试集上的得分要高。  \n",
    "而Lasso模型在测试集上的得分位于两者之间，因为它属于有偏估计，如果某些特征与结果的相关度不强，它的特征系数可以是0，从而产生稀疏解，在本例子中并不适用。如果在一些情况中，样本信息有限，我们用有限的信息去估计过多的系数，此时信息很可能会出现不够用的情况。应该选用Lasso模型，通过筛选变量提高估计效果。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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